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
2109.07799	Label-Attention Transformer with Geometrically Coherent Objects for Image Captioning	Automatic transcription of scene understanding in images and videos is a step towards artificial general intelligence. Image captioning is a nomenclature for describing meaningful information in an image using computer vision techniques. Automated image captioning techniques utilize encoder and decoder architecture, wh...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	255,658
2209.15555	Towards a Unified View of Affinity-Based Knowledge Distillation	Knowledge transfer between artificial neural networks has become an important topic in deep learning. Among the open questions are what kind of knowledge needs to be preserved for the transfer, and how it can be effectively achieved. Several recent work have shown good performance of distillation methods using relation...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	320,646
2312.00092	Mixture of Gaussian-distributed Prototypes with Generative Modelling for Interpretable and Trustworthy Image Recognition	Prototypical-part methods, e.g., ProtoPNet, enhance interpretability in image recognition by linking predictions to training prototypes, thereby offering intuitive insights into their decision-making. Existing methods, which rely on a point-based learning of prototypes, typically face two critical issues: 1) the learne...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,906
2501.06981	Data Enrichment Work and AI Labor in Latin America and the Caribbean	The global AI surge demands crowdworkers from diverse languages and cultures. They are pivotal in labeling data for enabling global AI systems. Despite global significance, research has primarily focused on understanding the perspectives and experiences of US and India crowdworkers, leaving a notable gap. To bridge thi...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	524,213
1206.3298	Continuous Time Dynamic Topic Models	In this paper, we develop the continuous time dynamic topic model (cDTM). The cDTM is a dynamic topic model that uses Brownian motion to model the latent topics through a sequential collection of documents, where a "topic" is a pattern of word use that we expect to evolve over the course of the collection. We derive an...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	16,555
2310.03186	Inferring Inference	Patterns of microcircuitry suggest that the brain has an array of repeated canonical computational units. Yet neural representations are distributed, so the relevant computations may only be related indirectly to single-neuron transformations. It thus remains an open challenge how to define canonical distributed comput...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	397,172
1810.10775	Adversarially Robust Optimization with Gaussian Processes	In this paper, we consider the problem of Gaussian process (GP) optimization with an added robustness requirement: The returned point may be perturbed by an adversary, and we require the function value to remain as high as possible even after this perturbation. This problem is motivated by settings in which the underly...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	111,361
2402.05066	Exploration Without Maps via Zero-Shot Out-of-Distribution Deep Reinforcement Learning	Operation of Autonomous Mobile Robots (AMRs) of all forms that include wheeled ground vehicles, quadrupeds and humanoids in dynamically changing GPS denied environments without a-priori maps, exclusively using onboard sensors, is an unsolved problem that has potential to transform the economy, and vastly improve humani...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	427,709
2110.13825	Synchronous-Clock Range-Angle Relative Acoustic Navigation: A Unified Approach to Multi-AUV Localization, Command, Control and Coordination	This paper presents a scalable acoustic navigation approach for the unified command, control and coordination of multiple autonomous underwater vehicles (AUVs). Existing multi-AUV operations typically achieve coordination manually, by programming individual vehicles on the surface via radio communications, which become...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	263,328
2311.16378	Bayesian Formulations for Graph Spectral Denoising	Here we consider the problem of denoising features associated to complex data, modeled as signals on a graph, via a smoothness prior. This is motivated in part by settings such as single-cell RNA where the data is very high-dimensional, but its structure can be captured via an affinity graph. This allows us to utilize ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	410,869
2402.03172	Accurate and Well-Calibrated ICD Code Assignment Through Attention Over Diverse Label Embeddings	Although the International Classification of Diseases (ICD) has been adopted worldwide, manually assigning ICD codes to clinical text is time-consuming, error-prone, and expensive, motivating the development of automated approaches. This paper describes a novel approach for automated ICD coding, combining several ideas...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	426,888
2101.09056	A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations	Counterfactual explanations provide a potentially significant solution to the Explainable AI (XAI) problem, but good, native counterfactuals have been shown to rarely occur in most datasets. Hence, the most popular methods generate synthetic counterfactuals using blind perturbation. However, such methods have several s...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	216,486
2310.13756	Learning Interatomic Potentials at Multiple Scales	The need to use a short time step is a key limit on the speed of molecular dynamics (MD) simulations. Simulations governed by classical potentials are often accelerated by using a multiple-time-step (MTS) integrator that evaluates certain potential energy terms that vary more slowly than others less frequently. This ap...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	401,562
1512.03219	Norm-Free Radon-Nikodym Approach to Machine Learning	For Machine Learning (ML) classification problem, where a vector of $\mathbf{x}$--observations (values of attributes) is mapped to a single $y$ value (class label), a generalized Radon--Nikodym type of solution is proposed. Quantum--mechanics --like probability states $\psi^2(\mathbf{x})$ are considered and "Cluster Ce...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	50,013
2310.12432	CAT: Closed-loop Adversarial Training for Safe End-to-End Driving	Driving safety is a top priority for autonomous vehicles. Orthogonal to prior work handling accident-prone traffic events by algorithm designs at the policy level, we investigate a Closed-loop Adversarial Training (CAT) framework for safe end-to-end driving in this paper through the lens of environment augmentation. CA...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	401,013
1912.05796	Automatic Layout Generation with Applications in Machine Learning Engine Evaluation	Machine learning-based lithography hotspot detection has been deeply studied recently, from varies feature extraction techniques to efficient learning models. It has been observed that such machine learning-based frameworks are providing satisfactory metal layer hotspot prediction results on known public metal layer be...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	157,195
2404.17175	Over-the-Air Modulation for RIS-assisted Symbiotic Radios: Design, Analysis, and Optimization	In reconfigurable intelligent surface (RIS)-assisted symbiotic radio (SR), an RIS is exploited to assist the primary system and to simultaneously operate as a secondary transmitter by modulating its own information over the incident primary signal from the air. Such an operation is called over-the-air modulation. The e...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	449,764
2211.06027	Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention	The binding problem is one of the fundamental challenges that prevent the artificial neural network (ANNs) from a compositional understanding of the world like human perception, because disentangled and distributed representations of generative factors can interfere and lead to ambiguity when complex data with multiple...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	329,760
2009.09277	Construction of Polar Codes with Reinforcement Learning	This paper formulates the polar-code construction problem for the successive-cancellation list (SCL) decoder as a maze-traversing game, which can be solved by reinforcement learning techniques. The proposed method provides a novel technique for polar-code construction that no longer depends on sorting and selecting bit...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	196,521
1907.07958	Transfer Learning Across Simulated Robots With Different Sensors	For a robot to learn a good policy, it often requires expensive equipment (such as sophisticated sensors) and a prepared training environment conducive to learning. However, it is seldom possible to perfectly equip robots for economic reasons, nor to guarantee ideal learning conditions, when deployed in real-life envir...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	139,005
2212.14161	Transactions Make Debugging Easy	We propose TROD, a novel transaction-oriented framework for debugging modern distributed web applications and online services. Our critical insight is that if applications store all state in databases and only access state transactionally, TROD can use lightweight always-on tracing to track the history of application s...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	338,526
2011.14469	Cyberphysical Security Through Resiliency: A Systems-centric Approach	Cyber-physical systems (CPS) are often defended in the same manner as information technology (IT) systems -- by using perimeter security. Multiple factors make such defenses insufficient for CPS. Resiliency shows potential in overcoming these shortfalls. Techniques for achieving resilience exist; however, methods and t...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	208,785
1912.00086	Learning Perceptual Inference by Contrasting	"Thinking in pictures," [1] i.e., spatial-temporal reasoning, effortless and instantaneous for humans, is believed to be a significant ability to perform logical induction and a crucial factor in the intellectual history of technology development. Modern Artificial Intelligence (AI), fueled by massive datasets, deeper ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	155,666
1104.1717	Continuous and Discrete Adjoints to the Euler Equations for Fluids	Adjoints are used in optimization to speed-up computations, simplify optimality conditions or compute sensitivities. Because time is reversed in adjoint equations with first order time derivatives, boundary conditions and transmission conditions through shocks can be difficult to understand. In this article we analyze ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	9,927
2112.01049	Bayesian Optimization over Permutation Spaces	Optimizing expensive to evaluate black-box functions over an input space consisting of all permutations of d objects is an important problem with many real-world applications. For example, placement of functional blocks in hardware design to optimize performance via simulations. The overall goal is to minimize the numb...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	269,355
2310.09382	LL-VQ-VAE: Learnable Lattice Vector-Quantization For Efficient Representations	In this paper we introduce learnable lattice vector quantization and demonstrate its effectiveness for learning discrete representations. Our method, termed LL-VQ-VAE, replaces the vector quantization layer in VQ-VAE with lattice-based discretization. The learnable lattice imposes a structure over all discrete embeddin...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	399,749
0912.4637	Local and Global Trust Based on the Concept of Promises	We use the notion of a promise to define local trust between agents possessing autonomous decision-making. An agent is trustworthy if it is expected that it will keep a promise. This definition satisfies most commonplace meanings of trust. Reputation is then an estimation of this expectation value that is passed on fro...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	5,209
2403.06798	Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification	Remarkable successes were made in Medical Image Classification (MIC) recently, mainly due to wide applications of convolutional neural networks (CNNs). However, adversarial examples (AEs) exhibited imperceptible similarity with raw data, raising serious concerns on network robustness. Although adversarial training (AT)...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	436,606
2212.06482	Over-The-Air Federated Learning Over Scalable Cell-free Massive MIMO	Cell-free massive MIMO is emerging as a promising technology for future wireless communication systems, which is expected to offer uniform coverage and high spectral efficiency compared to classical cellular systems. We study in this paper how cell-free massive MIMO can support federated edge learning. Taking advantage...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	336,128
1808.02082	Did you take the pill? - Detecting Personal Intake of Medicine from Twitter	Mining social media messages such as tweets, articles, and Facebook posts for health and drug related information has received significant interest in pharmacovigilance research. Social media sites (e.g., Twitter), have been used for monitoring drug abuse, adverse reactions of drug usage and analyzing expression of sen...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	104,700
2306.15065	Molecular geometric deep learning	Geometric deep learning (GDL) has demonstrated huge power and enormous potential in molecular data analysis. However, a great challenge still remains for highly efficient molecular representations. Currently, covalent-bond-based molecular graphs are the de facto standard for representing molecular topology at the atomi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	375,897
1804.08414	Abdominal multi-organ segmentation with organ-attention networks and statistical fusion	Accurate and robust segmentation of abdominal organs on CT is essential for many clinical applications such as computer-aided diagnosis and computer-aided surgery. But this task is challenging due to the weak boundaries of organs, the complexity of the background, and the variable sizes of different organs. To address ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	95,761
2003.13428	Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling	Information regarding precipitate shapes is critical for estimating material parameters. Hence, we considered estimating a region of material parameter space in which a computational model produces precipitates having shapes similar to those observed in the experimental images. This region, called the lower-error regio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	170,205
1704.05136	The Causality/Repair Connection in Databases: Causality-Programs	In this work, answer-set programs that specify repairs of databases are used as a basis for solving computational and reasoning problems about causes for query answers from databases.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	71,947
1907.05720	Wind Estimation Using Quadcopter Motion: A Machine Learning Approach	In this article, we study the well known problem of wind estimation in atmospheric turbulence using small unmanned aerial systems (sUAS). We present a machine learning approach to wind velocity estimation based on quadcopter state measurements without a wind sensor. We accomplish this by training a long short-term memo...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	138,442
2205.06355	Warm-starting DARTS using meta-learning	Neural architecture search (NAS) has shown great promise in the field of automated machine learning (AutoML). NAS has outperformed hand-designed networks and made a significant step forward in the field of automating the design of deep neural networks, thus further reducing the need for human expertise. However, most r...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	296,213
2406.15025	SiT: Symmetry-Invariant Transformers for Generalisation in Reinforcement Learning	An open challenge in reinforcement learning (RL) is the effective deployment of a trained policy to new or slightly different situations as well as semantically-similar environments. We introduce Symmetry-Invariant Transformer (SiT), a scalable vision transformer (ViT) that leverages both local and global data patterns...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	466,589
2306.13576	Penalty Gradient Normalization for Generative Adversarial Networks	In this paper, we propose a novel normalization method called penalty gradient normalization (PGN) to tackle the training instability of Generative Adversarial Networks (GANs) caused by the sharp gradient space. Unlike existing work such as gradient penalty and spectral normalization, the proposed PGN only imposes a pe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	375,325
2205.12609	Generating Information-Seeking Conversations from Unlabeled Documents	In this paper, we introduce a novel framework, SIMSEEK, (Simulating information-Seeking conversation from unlabeled documents), and compare its two variants. In our baseline SIMSEEK-SYM, a questioner generates follow-up questions upon the predetermined answer by an answerer. On the contrary, SIMSEEK-ASYM first generate...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	298,627
2012.10852	Visual Speech Enhancement Without A Real Visual Stream	In this work, we re-think the task of speech enhancement in unconstrained real-world environments. Current state-of-the-art methods use only the audio stream and are limited in their performance in a wide range of real-world noises. Recent works using lip movements as additional cues improve the quality of generated sp...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	212,456
1311.6215	Using virtual parts to optimize the metrology process	In the measurement process, there are many parameters affecting the measurement results: the influence of the probe system, material stiffness of measured workpiece, the calibration of the probe with a reference sphere, the thermal effects. We want to obtain the limits of a measurement methodology to be able to validat...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	28,633
1906.09302	Neural Machine Translating from Natural Language to SPARQL	SPARQL is a highly powerful query language for an ever-growing number of Linked Data resources and Knowledge Graphs. Using it requires a certain familiarity with the entities in the domain to be queried as well as expertise in the language's syntax and semantics, none of which average human web users can be assumed to ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	136,109
2410.05793	Distributed Coordination for Multi-Vehicle Systems in the Presence of Misbehaving Vehicles	The coordination problem of multi-vehicle systems is of great interests in the area of autonomous driving and multi-vehicle control. This work mainly focuses on multi-task coordination problem of a group of vehicles with a bicycle model and some specific control objectives, including collision avoidance, connectivity m...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	495,919
2012.04406	NavRep: Unsupervised Representations for Reinforcement Learning of Robot Navigation in Dynamic Human Environments	Robot navigation is a task where reinforcement learning approaches are still unable to compete with traditional path planning. State-of-the-art methods differ in small ways, and do not all provide reproducible, openly available implementations. This makes comparing methods a challenge. Recent research has shown that un...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	210,448
2202.00805	Context Uncertainty in Contextual Bandits with Applications to Recommender Systems	Recurrent neural networks have proven effective in modeling sequential user feedbacks for recommender systems. However, they usually focus solely on item relevance and fail to effectively explore diverse items for users, therefore harming the system performance in the long run. To address this problem, we propose a new...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	278,266
2212.07547	Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology	We propose a fully unsupervised method to detect bias in contextualized embeddings. The method leverages the assortative information latently encoded by social networks and combines orthogonality regularization, structured sparsity learning, and graph neural networks to find the embedding subspace capturing this inform...	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	false	false	false	336,430
1108.2096	Reputation-based Incentive Protocols in Crowdsourcing Applications	Crowdsourcing websites (e.g. Yahoo! Answers, Amazon Mechanical Turk, and etc.) emerged in recent years that allow requesters from all around the world to post tasks and seek help from an equally global pool of workers. However, intrinsic incentive problems reside in crowdsourcing applications as workers and requester a...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	true	11,618
2406.01140	Logical Reasoning with Relation Network for Inductive Knowledge Graph Completion	Inductive knowledge graph completion (KGC) aims to infer the missing relation for a set of newly-coming entities that never appeared in the training set. Such a setting is more in line with reality, as real-world KGs are constantly evolving and introducing new knowledge. Recent studies have shown promising results usin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	460,188
2208.00659	Model-based graph reinforcement learning for inductive traffic signal control	Most reinforcement learning methods for adaptive-traffic-signal-control require training from scratch to be applied on any new intersection or after any modification to the road network, traffic distribution, or behavioral constraints experienced during training. Considering 1) the massive amount of experience required...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	310,929
2109.08248	Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression	We use Gaussian stochastic weight averaging (SWAG) to assess the model-form uncertainty associated with neural-network-based function approximation relevant to fluid flows. SWAG approximates a posterior Gaussian distribution of each weight, given training data, and a constant learning rate. Having access to this distri...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	255,821
2107.13109	Pixyz: a Python library for developing deep generative models	With the recent rapid progress in the study of deep generative models (DGMs), there is a need for a framework that can implement them in a simple and generic way. In this research, we focus on two features of DGMs: (1) deep neural networks are encapsulated by probability distributions, and (2) models are designed and l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	248,099
1908.11197	Incorporating demand response of electric vehicles in scheduling of isolated microgrids with renewables using a bi-level programming approach	In this work, a novel optimal scheduling approach is proposed for isolated microgrids (MGs) with renewable generations by incorporating demand response of electric vehicles (EVs). First, a bi-level programming-based MG scheduling model is proposed under real-time pricing environments, where the upper- and lower- levels...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	143,314
2407.17638	Time Matters: Examine Temporal Effects on Biomedical Language Models	Time roots in applying language models for biomedical applications: models are trained on historical data and will be deployed for new or future data, which may vary from training data. While increasing biomedical tasks have employed state-of-the-art language models, there are very few studies have examined temporal ef...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	476,055
1804.00126	Snap Angle Prediction for 360$^{\circ}$ Panoramas	360$^{\circ}$ panoramas are a rich medium, yet notoriously difficult to visualize in the 2D image plane. We explore how intelligent rotations of a spherical image may enable content-aware projection with fewer perceptible distortions. Whereas existing approaches assume the viewpoint is fixed, intuitively some viewing a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,948
1805.07376	Algorithms for Estimating Trends in Global Temperature Volatility	Trends in terrestrial temperature variability are perhaps more relevant for species viability than trends in mean temperature. In this paper, we develop methodology for estimating such trends using multi-resolution climate data from polar orbiting weather satellites. We derive two novel algorithms for computation that ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	97,799
2211.12314	Attacking Image Splicing Detection and Localization Algorithms Using Synthetic Traces	Recent advances in deep learning have enabled forensics researchers to develop a new class of image splicing detection and localization algorithms. These algorithms identify spliced content by detecting localized inconsistencies in forensic traces using Siamese neural networks, either explicitly during analysis or impl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	332,066
2306.07919	Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations	Imitation learning has achieved great success in many sequential decision-making tasks, in which a neural agent is learned by imitating collected human demonstrations. However, existing algorithms typically require a large number of high-quality demonstrations that are difficult and expensive to collect. Usually, a tra...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	373,192
2412.06451	How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning	Uncertainty quantification (UQ) is essential for assessing the reliability of Earth observation (EO) products. However, the extensive use of machine learning models in EO introduces an additional layer of complexity, as those models themselves are inherently uncertain. While various UQ methods do exist for machine lear...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	515,249
1611.05154	Locomotion of the generalized Purcell's swimmer : Modelling, controllability and motion primitives	Micro-robotics at low Reynolds number has been a growing area of research over the past decade. We propose and study a generalized 3-link robotic swimmer inspired by the planar Purcell's swimmer. By incorporating out-of-plane motion of the outer limbs, this mechanism generalizes the planar Purcell's swimmer, which has ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	63,965
2412.07236	CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding	Electroencephalography (EEG) is a non-invasive technique to measure and record brain electrical activity, widely used in various BCI and healthcare applications. Early EEG decoding methods rely on supervised learning, limited by specific tasks and datasets, hindering model performance and generalizability. With the suc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	515,584
2208.06061	Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages	Machine translation has seen rapid progress with the advent of Transformer-based models. These models have no explicit linguistic structure built into them, yet they may still implicitly learn structured relationships by attending to relevant tokens. We hypothesize that this structural learning could be made more robus...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	312,579
2309.01104	Turn Fake into Real: Adversarial Head Turn Attacks Against Deepfake Detection	Malicious use of deepfakes leads to serious public concerns and reduces people's trust in digital media. Although effective deepfake detectors have been proposed, they are substantially vulnerable to adversarial attacks. To evaluate the detector's robustness, recent studies have explored various attacks. However, all e...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	true	389,546
2311.14756	Task-Distributionally Robust Data-Free Meta-Learning	Data-Free Meta-Learning (DFML) aims to efficiently learn new tasks by leveraging multiple pre-trained models without requiring their original training data. Existing inversion-based DFML methods construct pseudo tasks from a learnable dataset, which is inversely generated from the pre-trained model pool. For the first ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	410,243
0804.0924	A Unified Semi-Supervised Dimensionality Reduction Framework for Manifold Learning	We present a general framework of semi-supervised dimensionality reduction for manifold learning which naturally generalizes existing supervised and unsupervised learning frameworks which apply the spectral decomposition. Algorithms derived under our framework are able to employ both labeled and unlabeled examples and ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	1,539
2112.06694	Optimal Rate Adaption in Federated Learning with Compressed Communications	Federated Learning (FL) incurs high communication overhead, which can be greatly alleviated by compression for model updates. Yet the tradeoff between compression and model accuracy in the networked environment remains unclear and, for simplicity, most implementations adopt a fixed compression rate only. In this paper,...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	271,265
2305.01393	On Strong Secrecy for Multiple Access Channel with States and Causal CSI	Strong secrecy communication over a discrete memoryless state-dependent multiple access channel (SD-MAC) with an external eavesdropper is investigated. The channel is governed by discrete memoryless and i.i.d. channel states and the channel state information (CSI) is revealed to the encoders in a causal manner. An inne...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	361,659
2410.02067	DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation	In the realm of image generation, creating customized images from visual prompt with additional textual instruction emerges as a promising endeavor. However, existing methods, both tuning-based and tuning-free, struggle with interpreting the subject-essential attributes from the visual prompt. This leads to subject-irr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	494,080
1302.6934	Optimum Header Positioning in Successive Interference Cancellation (SIC) based Aloha	Random Access MAC protocols are simple and effective when the nature of the traffic is unpredictable and sporadic. In the following paper, investigations on the new Enhanced Contention Resolution ALOHA (ECRA) are presented, where some new aspects of the protocol are investigated. Mathematical derivation and numerical e...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	22,490
2311.04498	NExT-Chat: An LMM for Chat, Detection and Segmentation	The development of large language models (LLMs) has greatly advanced the field of multimodal understanding, leading to the emergence of large multimodal models (LMMs). In order to enhance the level of visual comprehension, recent studies have equipped LMMs with region-level understanding capabilities by representing ob...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	406,245
2502.14497	Stories that (are) Move(d by) Markets: A Causal Exploration of Market Shocks and Semantic Shifts across Different Partisan Groups	Macroeconomic fluctuations and the narratives that shape them form a mutually reinforcing cycle: public discourse can spur behavioural changes leading to economic shifts, which then result in changes in the stories that propagate. We show that shifts in semantic embedding space can be causally linked to financial marke...	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	535,857
2408.07865	Capturing the Complexity of Human Strategic Decision-Making with Machine Learning	Understanding how people behave in strategic settings--where they make decisions based on their expectations about the behavior of others--is a long-standing problem in the behavioral sciences. We conduct the largest study to date of strategic decision-making in the context of initial play in two-player matrix games, a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	480,751
0707.0799	A New Family of Unitary Space-Time Codes with a Fast Parallel Sphere Decoder Algorithm	In this paper we propose a new design criterion and a new class of unitary signal constellations for differential space-time modulation for multiple-antenna systems over Rayleigh flat-fading channels with unknown fading coefficients. Extensive simulations show that the new codes have significantly better performance th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	390
1710.10451	Sample-level CNN Architectures for Music Auto-tagging Using Raw Waveforms	Recent work has shown that the end-to-end approach using convolutional neural network (CNN) is effective in various types of machine learning tasks. For audio signals, the approach takes raw waveforms as input using an 1-D convolution layer. In this paper, we improve the 1-D CNN architecture for music auto-tagging by a...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	83,384
2412.19438	The Rendezvous Between Extreme Value Theory and Next-generation Networks	Promising technologies such as massive multiple-input and multiple-output, reconfigurable intelligent reflecting surfaces, non-terrestrial networks, millimetre wave communication, ultra-reliable lowlatency communication are envisioned as the enablers for next-generation (NG) networks. In contrast to conventional commun...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	520,841
2401.09323	BENO: Boundary-embedded Neural Operators for Elliptic PDEs	Elliptic partial differential equations (PDEs) are a major class of time-independent PDEs that play a key role in many scientific and engineering domains such as fluid dynamics, plasma physics, and solid mechanics. Recently, neural operators have emerged as a promising technique to solve elliptic PDEs more efficiently ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	422,217
2202.04947	OWL (Observe, Watch, Listen): Audiovisual Temporal Context for Localizing Actions in Egocentric Videos	Egocentric videos capture sequences of human activities from a first-person perspective and can provide rich multimodal signals. However, most current localization methods use third-person videos and only incorporate visual information. In this work, we take a deep look into the effectiveness of audiovisual context in ...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	279,720
2403.05546	Unified Occupancy on a Public Transport Network through Combination of AFC and APC Data	In a transport network, the onboard occupancy is key for gaining insights into travelers' habits and adjusting the offer. Traditionally, operators have relied on field studies to evaluate ridership of a typical workday. However, automated fare collection (AFC) and automatic passenger counting (APC) data, which provide ...	false	true	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	436,048
2304.11141	H2TF for Hyperspectral Image Denoising: Where Hierarchical Nonlinear Transform Meets Hierarchical Matrix Factorization	Recently, tensor singular value decomposition (t-SVD) has emerged as a promising tool for hyperspectral image (HSI) processing. In the t-SVD, there are two key building blocks: (i) the low-rank enhanced transform and (ii) the accompanying low-rank characterization of transformed frontal slices. Previous t-SVD methods m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	359,701
1807.00676	A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding	In this paper, we propose a novel space-time geometric representation of human landmark configurations and derive tools for comparison and classification. We model the temporal evolution of landmarks as parametrized trajectories on the Riemannian manifold of positive semidefinite matrices of fixed-rank. Our representat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	101,894
2209.10733	FusionRCNN: LiDAR-Camera Fusion for Two-stage 3D Object Detection	3D object detection with multi-sensors is essential for an accurate and reliable perception system of autonomous driving and robotics. Existing 3D detectors significantly improve the accuracy by adopting a two-stage paradigm which merely relies on LiDAR point clouds for 3D proposal refinement. Though impressive, the sp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	318,953
1107.3636	GPS Signal Acquisition via Compressive Multichannel Sampling	In this paper, we propose an efficient acquisition scheme for GPS receivers. It is shown that GPS signals can be effectively sampled and detected using a bank of randomized correlators with much fewer chip-matched filters than those used in existing GPS signal acquisition algorithms. The latter use correlations with al...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	11,350
2110.08515	Multimodal Dialogue Response Generation	Responsing with image has been recognized as an important capability for an intelligent conversational agent. Yet existing works only focus on exploring the multimodal dialogue models which depend on retrieval-based methods, but neglecting generation methods. To fill in the gaps, we first present a multimodal dialogue ...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	true	261,439
2004.05693	SFE-GACN: A Novel Unknown Attack Detection Method Using Intra Categories Generation in Embedding Space	In the encrypted network traffic intrusion detection, deep learning based schemes have attracted lots of attention. However, in real-world scenarios, data is often insufficient (few-shot), which leads to various deviations between the models prediction and the ground truth. Consequently, downstream tasks such as unknow...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	172,275
1804.08584	Leveraging Friendship Networks for Dynamic Link Prediction in Social Interaction Networks	On-line social networks (OSNs) often contain many different types of relationships between users. When studying the structure of OSNs such as Facebook, two of the most commonly studied networks are friendship and interaction networks. The link prediction problem in friendship networks has been heavily studied. There ha...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	95,790
2204.00791	CL-XABSA: Contrastive Learning for Cross-lingual Aspect-based Sentiment Analysis	As an extensive research in the field of natural language processing (NLP), aspect-based sentiment analysis (ABSA) is the task of predicting the sentiment expressed in a text relative to the corresponding aspect. Unfortunately, most languages lack sufficient annotation resources, thus more and more recent researchers f...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	289,385
1905.10309	Unsupervised Machine Learning for the Discovery of Latent Disease Clusters and Patient Subgroups Using Electronic Health Records	Machine learning has become ubiquitous and a key technology on mining electronic health records (EHRs) for facilitating clinical research and practice. Unsupervised machine learning, as opposed to supervised learning, has shown promise in identifying novel patterns and relations from EHRs without using human created la...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	132,018
2312.06123	Efficient Estimation of Pairwise Effective Resistance	Given an undirected graph G, the effective resistance r(s,t) measures the dissimilarity of node pair s,t in G, which finds numerous applications in real-world problems, such as recommender systems, combinatorial optimization, molecular chemistry, and electric power networks. Existing techniques towards pairwise effecti...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	false	414,380
2205.11261	An Elastic Ephemeral Datastore using Cheap, Transient Cloud Resources	Spot instances are virtual machines offered at 60-90% lower cost that can be reclaimed at any time, with only a short warning period. Spot instances have already been used to significantly reduce the cost of processing workloads in the cloud. However, leveraging spot instances to reduce the cost of stateful cloud appli...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	298,076
2301.06622	IOPathTune: Adaptive Online Parameter Tuning for Parallel File System I/O Path	Parallel file systems contain complicated I/O paths from clients to storage servers. An efficient I/O path requires proper settings of multiple parameters, as the default settings often fail to deliver optimal performance, especially for diverse workloads in the HPC environment. Existing tuning strategies have shortcom...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	340,687
1911.00718	On secure communication in sensor networks under q-composite key predistribution with unreliable links	Many applications of wireless sensor networks (WSNs) require deploying sensors in hostile environments, where an adversary may eavesdrop communications. To secure communications in WSNs, the q-composite key predistribution scheme has been proposed in the literature. In this paper, we investigate secure k-connectivity i...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	151,899
2205.12427	Non-stationary Bandits with Knapsacks	In this paper, we study the problem of bandits with knapsacks (BwK) in a non-stationary environment. The BwK problem generalizes the multi-arm bandit (MAB) problem to model the resource consumption associated with playing each arm. At each time, the decision maker/player chooses to play an arm, and s/he will receive a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	298,530
2107.13236	Social media emotion macroscopes reflect emotional experiences in society at large	Social media generate data on human behaviour at large scales and over long periods of time, posing a complementary approach to traditional methods in the social sciences. Millions of texts from social media can be processed with computational methods to study emotions over time and across regions. However, recent rese...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	248,141
1912.11082	Scalable Fine-grained Generated Image Classification Based on Deep Metric Learning	Recently, generated images could reach very high quality, even human eyes could not tell them apart from real images. Although there are already some methods for detecting generated images in current forensic community, most of these methods are used to detect a single type of generated images. The new types of generat...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	158,477
2207.13882	SuperVessel: Segmenting High-resolution Vessel from Low-resolution Retinal Image	Vascular segmentation extracts blood vessels from images and serves as the basis for diagnosing various diseases, like ophthalmic diseases. Ophthalmologists often require high-resolution segmentation results for analysis, which leads to super-computational load by most existing methods. If based on low-resolution input...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	310,435
2112.00491	An Age of Information Characterization of Frameless ALOHA	We provide a characterization of the peak age of information (AoI) achievable in a random-access system operating according to the frameless ALOHA protocol. Differently from previous studies, our analysis accounts for the fact that the number of terminals contending the channel may vary over time, as a function of the ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	269,152
1809.04458	Unsupervised Representation Learning of Speech for Dialect Identification	In this paper, we explore the use of a factorized hierarchical variational autoencoder (FHVAE) model to learn an unsupervised latent representation for dialect identification (DID). An FHVAE can learn a latent space that separates the more static attributes within an utterance from the more dynamic attributes by encodi...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	107,573
2311.15474	Demonstration of Programmable Brain-Inspired Optoelectronic Neuron in Photonic Spiking Neural Network with Neural Heterogeneity	Photonic Spiking Neural Networks (PSNN) composed of the co-integrated CMOS and photonic elements can offer low loss, low power, highly-parallel, and high-throughput computing for brain-inspired neuromorphic systems. In addition, heterogeneity of neuron dynamics can also bring greater diversity and expressivity to brain...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	410,520
2304.08597	eTOP: Early Termination of Pipelines for Faster Training of AutoML Systems	Recent advancements in software and hardware technologies have enabled the use of AI/ML models in everyday applications has significantly improved the quality of service rendered. However, for a given application, finding the right AI/ML model is a complex and costly process, that involves the generation, training, and...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	358,766
2206.07160	LAVENDER: Unifying Video-Language Understanding as Masked Language Modeling	Unified vision-language frameworks have greatly advanced in recent years, most of which adopt an encoder-decoder architecture to unify image-text tasks as sequence-to-sequence generation. However, existing video-language (VidL) models still require task-specific designs in model architecture and training objectives for...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	302,619
2408.02654	On Using Quasirandom Sequences in Machine Learning for Model Weight Initialization	The effectiveness of training neural networks directly impacts computational costs, resource allocation, and model development timelines in machine learning applications. An optimizer's ability to train the model adequately (in terms of trained model performance) depends on the model's initial weights. Model weight ini...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	478,705

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