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
1702.01386	Joint DOA and Frequency Estimation with Sub-Nyquist Sampling for More Sources than Sensors	In this letter, we apply previous array receiver architecture which employs time-domain sub-Nyquist sampling techniques to jointly estimate frequency and direction-of-arrival(DOA) of narrowband far-field signals. Herein, a more general situation is taken into consideration, where there may be more than one signal in a ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,804
2405.12312	A Principled Approach for a New Bias Measure	The widespread use of machine learning and data-driven algorithms for decision making has been steadily increasing over many years. The areas in which this is happening are diverse: healthcare, employment, finance, education, the legal system to name a few; and the associated negative side effects are being increasingl...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	455,473
2310.01853	Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model	Data assimilation addresses the problem of identifying plausible state trajectories of dynamical systems given noisy or incomplete observations. In geosciences, it presents challenges due to the high-dimensionality of geophysical dynamical systems, often exceeding millions of dimensions. This work assesses the scalabil...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	396,608
2301.01037	Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings	In this work, we tackle the problem of adapting a real-time recommender system to multiple application domains, and their underlying data models and customization requirements. To do that, we present Uptrendz, a multi-domain recommendation platform that can be customized to provide real-time recommendations in an API-c...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	339,112
2312.15160	Human-AI Collaboration in Real-World Complex Environment with Reinforcement Learning	Recent advances in reinforcement learning (RL) and Human-in-the-Loop (HitL) learning have made human-AI collaboration easier for humans to team with AI agents. Leveraging human expertise and experience with AI in intelligent systems can be efficient and beneficial. Still, it is unclear to what extent human-AI collabora...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	417,896
1609.01982	Uniform Transformation of Non-Separable Probability Distributions	A theoretical framework is developed to describe the transformation that distributes probability density functions uniformly over space. In one dimension, the cumulative distribution can be used, but does not generalize to higher dimensions, or non-separable distributions. A potential function is shown to link probabil...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	60,664
1608.00293	Left-corner Methods for Syntactic Modeling with Universal Structural Constraints	The primary goal in this thesis is to identify better syntactic constraint or bias, that is language independent but also efficiently exploitable during sentence processing. We focus on a particular syntactic construction called center-embedding, which is well studied in psycholinguistics and noted to cause particular ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	59,263
2412.06685	Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone	Recent advances in learning decision-making policies can largely be attributed to training expressive policy models, largely via imitation learning. While imitation learning discards non-expert data, reinforcement learning (RL) can still learn from suboptimal data. However, instantiating RL training of a new policy cla...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	515,329
1810.10769	Expedition: A Time-Aware Exploratory Search System Designed for Scholars	Archives are an important source of study for various scholars. Digitization and the web have made archives more accessible and led to the development of several time-aware exploratory search systems. However these systems have been designed for more general users rather than scholars. Scholars have more complex inform...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	111,359
2404.04892	Elementary fractal geometry. 5. Weak separation is strong separation	For self-similar sets, there are two important separation properties: the open set condition and the weak separation condition introduced by Zerner, which may be replaced by the formally stronger finite type property of Ngai and Wang. We show that any finite type self-similar set can be represented as a graph-directed ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	444,846
1604.04004	Understanding How Image Quality Affects Deep Neural Networks	Image quality is an important practical challenge that is often overlooked in the design of machine vision systems. Commonly, machine vision systems are trained and tested on high quality image datasets, yet in practical applications the input images can not be assumed to be of high quality. Recently, deep neural netwo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,583
1905.01553	An End-to-End Framework to Identify Pathogenic Social Media Accounts on Twitter	Pathogenic Social Media (PSM) accounts such as terrorist supporter accounts and fake news writers have the capability of spreading disinformation to viral proportions. Early detection of PSM accounts is crucial as they are likely to be key users to make malicious information "viral". In this paper, we adopt the causal ...	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	false	129,745
2210.03624	KAST: Knowledge Aware Adaptive Session Multi-Topic Network for Click-Through Rate Prediction	Capturing the evolving trends of user interest is important for both recommendation systems and advertising systems, and user behavior sequences have been successfully used in Click-Through-Rate(CTR) prediction problems. However, if the user interest is learned on the basis of item-level behaviors, the performance may ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	322,111
2106.03428	Automation for Interpretable Machine Learning Through a Comparison of Loss Functions to Regularisers	To increase the ubiquity of machine learning it needs to be automated. Automation is cost-effective as it allows experts to spend less time tuning the approach, which leads to shorter development times. However, while this automation produces highly accurate architectures, they can be uninterpretable, acting as `black-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	239,317
1808.03591	How Complex is your classification problem? A survey on measuring classification complexity	Characteristics extracted from the training datasets of classification problems have proven to be effective predictors in a number of meta-analyses. Among them, measures of classification complexity can be used to estimate the difficulty in separating the data points into their expected classes. Descriptors of the spat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	104,959
2002.10330	FSinR: an exhaustive package for feature selection	Feature Selection (FS) is a key task in Machine Learning. It consists in selecting a number of relevant variables for the model construction or data analysis. We present the R package, FSinR, which implements a variety of widely known filter and wrapper methods, as well as search algorithms. Thus, the package provides ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	165,369
2311.09753	DIFFNAT: Improving Diffusion Image Quality Using Natural Image Statistics	Diffusion models have advanced generative AI significantly in terms of editing and creating naturalistic images. However, efficiently improving generated image quality is still of paramount interest. In this context, we propose a generic "naturalness" preserving loss function, viz., kurtosis concentration (KC) loss, wh...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,275
1904.09747	Local Deep-Feature Alignment for Unsupervised Dimension Reduction	This paper presents an unsupervised deep-learning framework named Local Deep-Feature Alignment (LDFA) for dimension reduction. We construct neighbourhood for each data sample and learn a local Stacked Contractive Auto-encoder (SCAE) from the neighbourhood to extract the local deep features. Next, we exploit an affine t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,471
1809.01263	An Efficient Approach for Polyps Detection in Endoscopic Videos Based on Faster R-CNN	Polyp has long been considered as one of the major etiologies to colorectal cancer which is a fatal disease around the world, thus early detection and recognition of polyps plays a crucial role in clinical routines. Accurate diagnoses of polyps through endoscopes operated by physicians becomes a challenging task not on...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	106,759
1704.00390	Geometric Loss Functions for Camera Pose Regression with Deep Learning	Deep learning has shown to be effective for robust and real-time monocular image relocalisation. In particular, PoseNet is a deep convolutional neural network which learns to regress the 6-DOF camera pose from a single image. It learns to localize using high level features and is robust to difficult lighting, motion bl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,074
1905.04833	Learning and Planning in the Feature Deception Problem	Today's high-stakes adversarial interactions feature attackers who constantly breach the ever-improving security measures. Deception mitigates the defender's loss by misleading the attacker to make suboptimal decisions. In order to formally reason about deception, we introduce the feature deception problem (FDP), a dom...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	true	130,577
1207.1067	Bounding differences in Jager Pairs	Symmetrical subdivisions in the space of Jager Pairs for continued fractions-like expansions will provide us with bounds on their difference. Results will also apply to the classical regular and backwards continued fractions expansions, which are realized as special cases.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	17,215
2403.15684	The Limits of Perception: Analyzing Inconsistencies in Saliency Maps in XAI	Explainable artificial intelligence (XAI) plays an indispensable role in demystifying the decision-making processes of AI, especially within the healthcare industry. Clinicians rely heavily on detailed reasoning when making a diagnosis, often CT scans for specific features that distinguish between benign and malignant ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,691
1903.06741	Analysis of a Stochastic Model for Coordinated Platooning of Heavy-duty Vehicles	Platooning of heavy-duty vehicles (HDVs) is a key component of smart and connected highways and is expected to bring remarkable fuel savings and emission reduction. In this paper, we study the coordination of HDV platooning on a highway section. We model the arrival of HDVs as a Poisson process. Multiple HDVs are merge...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	124,451
1804.06253	Temporal Coherent and Graph Optimized Manifold Ranking for Visual Tracking	Recently, weighted patch representation has been widely studied for alleviating the impact of background information included in bounding box to improve visual tracking results. However, existing weighted patch representation models generally exploit spatial structure information among patches in each frame separately ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	95,259
2412.19645	VideoMaker: Zero-shot Customized Video Generation with the Inherent Force of Video Diffusion Models	Zero-shot customized video generation has gained significant attention due to its substantial application potential. Existing methods rely on additional models to extract and inject reference subject features, assuming that the Video Diffusion Model (VDM) alone is insufficient for zero-shot customized video generation....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	520,919
2202.06914	A Generic Self-Supervised Framework of Learning Invariant Discriminative Features	Self-supervised learning (SSL) has become a popular method for generating invariant representations without the need for human annotations. Nonetheless, the desired invariant representation is achieved by utilising prior online transformation functions on the input data. As a result, each SSL framework is customised fo...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	280,371
2107.11768	A Joint and Domain-Adaptive Approach to Spoken Language Understanding	Spoken Language Understanding (SLU) is composed of two subtasks: intent detection (ID) and slot filling (SF). There are two lines of research on SLU. One jointly tackles these two subtasks to improve their prediction accuracy, and the other focuses on the domain-adaptation ability of one of the subtasks. In this paper,...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	247,688
2108.00856	A mechanism-based multi-trap phase field model for hydrogen assisted fracture	We present a new mechanistic, phase field-based formulation for predicting hydrogen embrittlement. The multi-physics model developed incorporates, for the first time, a Taylor-based dislocation model to resolve the mechanics of crack tip deformation. This enables capturing the role of dislocation hardening mechanisms i...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	248,850
2404.19040	GSTalker: Real-time Audio-Driven Talking Face Generation via Deformable Gaussian Splatting	We present GStalker, a 3D audio-driven talking face generation model with Gaussian Splatting for both fast training (40 minutes) and real-time rendering (125 FPS) with a 3$\sim$5 minute video for training material, in comparison with previous 2D and 3D NeRF-based modeling frameworks which require hours of training and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	450,479
1901.07928	Approximate k-Cover in Hypergraphs: Efficient Algorithms, and Applications	Given a weighted hypergraph $\mathcal{H}(V, \mathcal{E} \subseteq 2^V, w)$, the approximate $k$-cover problem seeks for a size-$k$ subset of $V$ that has the maximum weighted coverage by \emph{sampling only a few hyperedges} in $\mathcal{E}$. The problem has emerged from several network analysis applications including ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	119,342
0805.4508	Modeling Loosely Annotated Images with Imagined Annotations	In this paper, we present an approach to learning latent semantic analysis models from loosely annotated images for automatic image annotation and indexing. The given annotation in training images is loose due to: (1) ambiguous correspondences between visual features and annotated keywords; (2) incomplete lists of anno...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	1,845
2310.11645	Towards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos using NeRFs	Given that a conventional laparoscope only provides a two-dimensional (2-D) view, the detection and diagnosis of medical ailments can be challenging. To overcome the visual constraints associated with laparoscopy, the use of laparoscopic images and videos to reconstruct the three-dimensional (3-D) anatomical structure ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	400,717
2202.07135	Compositional Scene Representation Learning via Reconstruction: A Survey	Visual scenes are composed of visual concepts and have the property of combinatorial explosion. An important reason for humans to efficiently learn from diverse visual scenes is the ability of compositional perception, and it is desirable for artificial intelligence to have similar abilities. Compositional scene repres...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	280,444
2408.04174	wav2graph: A Framework for Supervised Learning Knowledge Graph from Speech	Knowledge graphs (KGs) enhance the performance of large language models (LLMs) and search engines by providing structured, interconnected data that improves reasoning and context-awareness. However, KGs only focus on text data, thereby neglecting other modalities such as speech. In this work, we introduce wav2graph, th...	false	false	true	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	479,274
2008.08906	Cooperative Multi-Point Vehicular Positioning Using Millimeter-Wave Surface Reflection (Extended version)	Multi-point vehicular positioning is one essential operation for autonomous vehicles. However, the state-of-the-art positioning technologies, relying on reflected signals from a target (i.e., RADAR and LIDAR), cannot work without line-of-sight. Besides, it takes significant time for environment scanning and object reco...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	192,543
1810.09923	Learning Classical Planning Strategies with Policy Gradient	A common paradigm in classical planning is heuristic forward search. Forward search planners often rely on simple best-first search which remains fixed throughout the search process. In this paper, we introduce a novel search framework capable of alternating between several forward search approaches while solving a par...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	111,153
2502.01188	FairUDT: Fairness-aware Uplift Decision Trees	Training data used for developing machine learning classifiers can exhibit biases against specific protected attributes. Such biases typically originate from historical discrimination or certain underlying patterns that disproportionately under-represent minority groups, such as those identified by their gender, religi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	529,740
2309.12744	Open Source Robot Localization for Non-Planar Environments	The operational environments in which a mobile robot executes its missions often exhibit non-flat terrain characteristics, encompassing outdoor and indoor settings featuring ramps and slopes. In such scenarios, the conventional methodologies employed for localization encounter novel challenges and limitations. This stu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	393,920
2410.04923	Integrated or Segregated? User Behavior Change after Cross-Party Interactions on Reddit	It has been a widely shared concern that social media reinforces echo chambers of like-minded users and exacerbate political polarization. While fostering interactions across party lines is recognized as an important strategy to break echo chambers, there is a lack of empirical evidence on whether users will actually b...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	495,496
2312.09264	A Categorical Model for Classical and Quantum Block Designs	Classical block designs are important combinatorial structures with a wide range of applications in Computer Science and Statistics. Here we give a new abstract description of block designs based on the arrow category construction. We show that models of this structure in the category of matrices and natural numbers re...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	415,660
2303.17218	HARFLOW3D: A Latency-Oriented 3D-CNN Accelerator Toolflow for HAR on FPGA Devices	For Human Action Recognition tasks (HAR), 3D Convolutional Neural Networks have proven to be highly effective, achieving state-of-the-art results. This study introduces a novel streaming architecture based toolflow for mapping such models onto FPGAs considering the model's inherent characteristics and the features of t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	355,143
2006.13261	Fast Optimization of Temperature Focusing in Hyperthermia Treatment of Sub-Superficial Tumors	Microwave hyperthermia aims at selectively heating cancer cells to a supra-physiological temperature. For non-superficial tumors, this can be achieved by means of an antenna array equipped with a proper cooling system (the water bolus) to avoid overheating of the skin. In patient-specific treatment planning, antenna fe...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	183,843
2201.04042	Towards Lightweight Neural Animation : Exploration of Neural Network Pruning in Mixture of Experts-based Animation Models	In the past few years, neural character animation has emerged and offered an automatic method for animating virtual characters. Their motion is synthesized by a neural network. Controlling this movement in real time with a user-defined control signal is also an important task in video games for example. Solutions based...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	275,001
1008.5373	Penalty Decomposition Methods for Rank Minimization	In this paper we consider general rank minimization problems with rank appearing in either objective function or constraint. We first establish that a class of special rank minimization problems has closed-form solutions. Using this result, we then propose penalty decomposition methods for general rank minimization pro...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	7,425
1911.00506	Six constructions of asymptotically optimal codebooks via the character sums	In this paper, using additive characters of finite field, we find a codebook which is equivalent to the measurement matrix in [20]. The advantage of our construction is that it can be generalized naturally to construct the other five classes of codebooks using additive and multiplicative characters of finite field. We ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	151,837
1306.4391	On the Fundamental Limits of Recovering Tree Sparse Vectors from Noisy Linear Measurements	Recent breakthrough results in compressive sensing (CS) have established that many high dimensional signals can be accurately recovered from a relatively small number of non-adaptive linear observations, provided that the signals possess a sparse representation in some basis. Subsequent efforts have shown that the perf...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	25,301
2102.07645	Freudian and Newtonian Recurrent Cell for Sequential Recommendation	A sequential recommender system aims to recommend attractive items to users based on behaviour patterns. The predominant sequential recommendation models are based on natural language processing models, such as the gated recurrent unit, that embed items in some defined space and grasp the user's long-term and short-ter...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	220,172
2407.05312	An Improved Method for Personalizing Diffusion Models	Diffusion models have demonstrated impressive image generation capabilities. Personalized approaches, such as textual inversion and Dreambooth, enhance model individualization using specific images. These methods enable generating images of specific objects based on diverse textual contexts. Our proposed approach aims ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,917
2410.00772	On the Generalization and Causal Explanation in Self-Supervised Learning	Self-supervised learning (SSL) methods learn from unlabeled data and achieve high generalization performance on downstream tasks. However, they may also suffer from overfitting to their training data and lose the ability to adapt to new tasks. To investigate this phenomenon, we conduct experiments on various SSL method...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	493,496
2409.14882	Probabilistically Aligned View-unaligned Clustering with Adaptive Template Selection	In most existing multi-view modeling scenarios, cross-view correspondence (CVC) between instances of the same target from different views, like paired image-text data, is a crucial prerequisite for effortlessly deriving a consistent representation. Nevertheless, this premise is frequently compromised in certain applica...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	490,674
2405.11675	Deep Ensemble Art Style Recognition	The massive digitization of artworks during the last decades created the need for categorization, analysis, and management of huge amounts of data related to abstract concepts, highlighting a challenging problem in the field of computer science. The rapid progress of artificial intelligence and neural networks has prov...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	455,235
2501.11833	Is your LLM trapped in a Mental Set? Investigative study on how mental sets affect the reasoning capabilities of LLMs	In this paper, we present an investigative study on how Mental Sets influence the reasoning capabilities of LLMs. LLMs have excelled in diverse natural language processing (NLP) tasks, driven by advancements in parameter-efficient fine-tuning (PEFT) and emergent capabilities like in-context learning (ICL). For complex ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	526,054
2312.06551	Successive Bayesian Reconstructor for Channel Estimation in Fluid Antenna Systems	Fluid antenna systems (FASs) can reconfigure their antenna locations freely within a spatially continuous space. To keep favorable antenna positions, the channel state information (CSI) acquisition for FASs is essential. While some techniques have been proposed, most existing FAS channel estimators require several chan...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	414,562
2206.12414	Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes	A large fraction of data generated via human activities such as online purchases, health records, spatial mobility etc. can be represented as a sequence of events over a continuous-time. Learning deep learning models over these continuous-time event sequences is a non-trivial task as it involves modeling the ever-incre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	304,592
2407.01408	Semantic Compositions Enhance Vision-Language Contrastive Learning	In the field of vision-language contrastive learning, models such as CLIP capitalize on matched image-caption pairs as positive examples and leverage within-batch non-matching pairs as negatives. This approach has led to remarkable outcomes in zero-shot image classification, cross-modal retrieval, and linear evaluation...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	469,284
2311.10221	An Active-Sensing Approach for Bearing-based Target Localization	Characterized by a cross-disciplinary nature, the bearing-based target localization task involves estimating the position of an entity of interest by a group of agents capable of collecting noisy bearing measurements. In this work, this problem is tackled by resting both on the weighted least square estimation approach...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	408,449
2409.01392	ComfyBench: Benchmarking LLM-based Agents in ComfyUI for Autonomously Designing Collaborative AI Systems	Much previous AI research has focused on developing monolithic models to maximize their intelligence, with the primary goal of enhancing performance on specific tasks. In contrast, this work attempts to study using LLM-based agents to design collaborative AI systems autonomously. To explore this problem, we first intro...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	485,320
2312.00778	MorpheuS: Neural Dynamic 360{\deg} Surface Reconstruction from Monocular RGB-D Video	Neural rendering has demonstrated remarkable success in dynamic scene reconstruction. Thanks to the expressiveness of neural representations, prior works can accurately capture the motion and achieve high-fidelity reconstruction of the target object. Despite this, real-world video scenarios often feature large unobserv...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,167
2212.12204	EndoBoost: a plug-and-play module for false positive suppression during computer-aided polyp detection in real-world colonoscopy (with dataset)	The advance of computer-aided detection systems using deep learning opened a new scope in endoscopic image analysis. However, the learning-based models developed on closed datasets are susceptible to unknown anomalies in complex clinical environments. In particular, the high false positive rate of polyp detection remai...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	337,990
1805.00521	Direct Runge-Kutta Discretization Achieves Acceleration	We study gradient-based optimization methods obtained by directly discretizing a second-order ordinary differential equation (ODE) related to the continuous limit of Nesterov's accelerated gradient method. When the function is smooth enough, we show that acceleration can be achieved by a stable discretization of this O...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	96,453
2005.05245	Periodic optimal control of nonlinear constrained systems using economic model predictive control	In this paper, we consider the problem of periodic optimal control of nonlinear systems subject to online changing and periodically time-varying economic performance measures using model predictive control (MPC). The proposed economic MPC scheme uses an online optimized artificial periodic orbit to ensure recursive fea...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	176,682
2305.05848	Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation	Recommender systems are essential to various fields, e.g., e-commerce, e-learning, and streaming media. At present, graph neural networks (GNNs) for session-based recommendations normally can only recommend items existing in users' historical sessions. As a result, these GNNs have difficulty recommending items that use...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	363,309
2110.03146	Solving Multistage Stochastic Linear Programming via Regularized Linear Decision Rules: An Application to Hydrothermal Dispatch Planning	The solution of multistage stochastic linear problems (MSLP) represents a challenge for many application areas. Long-term hydrothermal dispatch planning (LHDP) materializes this challenge in a real-world problem that affects electricity markets, economies, and natural resources worldwide. No closed-form solutions are a...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	259,383
1803.05494	Improving Object Counting with Heatmap Regulation	In this paper, we propose a simple and effective way to improve one-look regression models for object counting from images. We use class activation map visualizations to illustrate the drawbacks of learning a pure one-look regression model for a counting task. Based on these insights, we enhance one-look regression cou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	92,643
1706.07888	Evolving Spatially Aggregated Features from Satellite Imagery for Regional Modeling	Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a novel method of inducing spatial aggregations as a component of the machine lea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	75,911
2312.16483	Expressivity and Approximation Properties of Deep Neural Networks with ReLU$^k$ Activation	In this paper, we investigate the expressivity and approximation properties of deep neural networks employing the ReLU$^k$ activation function for $k \geq 2$. Although deep ReLU networks can approximate polynomials effectively, deep ReLU$^k$ networks have the capability to represent higher-degree polynomials precisely....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	418,401
2302.10023	Arena-Rosnav 2.0: A Development and Benchmarking Platform for Robot Navigation in Highly Dynamic Environments	Following up on our previous works, in this paper, we present Arena-Rosnav 2.0 an extension to our previous works Arena-Bench and Arena-Rosnav, which adds a variety of additional modules for developing and benchmarking robotic navigation approaches. The platform is fundamentally restructured and provides unified APIs t...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	346,655
2105.13878	Accelerating BERT Inference for Sequence Labeling via Early-Exit	Both performance and efficiency are crucial factors for sequence labeling tasks in many real-world scenarios. Although the pre-trained models (PTMs) have significantly improved the performance of various sequence labeling tasks, their computational cost is expensive. To alleviate this problem, we extend the recent succ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	237,439
1910.10147	Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe	A method for machine learning and serving of discrete field theories in physics is developed. The learning algorithm trains a discrete field theory from a set of observational data on a spacetime lattice, and the serving algorithm uses the learned discrete field theory to predict new observations of the field for new b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	150,408
2301.03283	A Robust Multilabel Method Integrating Rule-based Transparent Model, Soft Label Correlation Learning and Label Noise Resistance	Model transparency, label correlation learning and the robust-ness to label noise are crucial for multilabel learning. However, few existing methods study these three characteristics simultaneously. To address this challenge, we propose the robust multilabel Takagi-Sugeno-Kang fuzzy system (R-MLTSK-FS) with three mecha...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	339,749
1902.04024	Reactive Control Meets Runtime Verification: A Case Study of Navigation	This paper presents an application of specification based runtime verification techniques to control mobile robots in a reactive manner. In our case study, we develop a layered control architecture where runtime monitors constructed from formal specifications are embedded into the navigation stack. We use temporal logi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	121,246
2006.12812	An Efficient Index for Contact Tracing Query in a Large Spatio-Temporal Database	In this paper, we study a novel contact tracing query (CTQ) that finds users who have been in $direct$ $contact$ with the query user or $in$ $contact$ $with$ $the$ $already$ $contacted$ $users$ in subsequent timestamps from a large spatio-temporal database. The CTQ is of paramount importance in the era of new COVID-19 ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	183,719
2011.10529	Computation capacities of a broad class of signaling networks are higher than their communication capacities	Due to structural and functional abnormalities or genetic variations and mutations, there may be dysfunctional molecules within an intracellular signaling network that do not allow the network to correctly regulate its output molecules, such as transcription factors. This disruption in signaling interrupts normal cellu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	207,537
2405.12438	CoCo Matrix: Taxonomy of Cognitive Contributions in Co-writing with Intelligent Agents	In recent years, there has been a growing interest in employing intelligent agents in writing. Previous work emphasizes the evaluation of the quality of end product-whether it was coherent and polished, overlooking the journey that led to the product, which is an invaluable dimension of the creative process. To underst...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	455,519
1207.0658	On the origin of long-range correlations in texts	The complexity of human interactions with social and natural phenomena is mirrored in the way we describe our experiences through natural language. In order to retain and convey such a high dimensional information, the statistical properties of our linguistic output has to be highly correlated in time. An example are t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	17,184
2204.13386	Self-supervised Contrastive Learning for Audio-Visual Action Recognition	The underlying correlation between audio and visual modalities can be utilized to learn supervised information for unlabeled videos. In this paper, we propose an end-to-end self-supervised framework named Audio-Visual Contrastive Learning (AVCL), to learn discriminative audio-visual representations for action recogniti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,805
2306.02002	Can Directed Graph Neural Networks be Adversarially Robust?	The existing research on robust Graph Neural Networks (GNNs) fails to acknowledge the significance of directed graphs in providing rich information about networks' inherent structure. This work presents the first investigation into the robustness of GNNs in the context of directed graphs, aiming to harness the profound...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	370,714
1802.01345	DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text	Existing text generation methods tend to produce repeated and "boring" expressions. To tackle this problem, we propose a new text generation model, called Diversity-Promoting Generative Adversarial Network (DP-GAN). The proposed model assigns low reward for repeatedly generated text and high reward for "novel" and flue...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	89,590
2104.08337	Identification of mental fatigue in language comprehension tasks based on EEG and deep learning	Mental fatigue increases the risk of operator error in language comprehension tasks. In order to prevent operator performance degradation, we used EEG signals to assess the mental fatigue of operators in human-computer systems. This study presents an experimental design for fatigue detection in language comprehension t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	230,755
cs/0309016	Using Simulated Annealing to Calculate the Trembles of Trembling Hand Perfection	Within the literature on non-cooperative game theory, there have been a number of attempts to propose logorithms which will compute Nash equilibria. Rather than derive a new algorithm, this paper shows that the family of algorithms known as Markov chain Monte Carlo (MCMC) can be used to calculate Nash equilibria. MCMC ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	537,981
2311.12046	LATIS: Lambda Abstraction-based Thermal Image Super-resolution	Single image super-resolution (SISR) is an effective technique to improve the quality of low-resolution thermal images. Recently, transformer-based methods have achieved significant performance in SISR. However, in the SR task, only a small number of pixels are involved in the transformers self-attention (SA) mechanism...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	409,174
1911.05916	Adversarial Margin Maximization Networks	The tremendous recent success of deep neural networks (DNNs) has sparked a surge of interest in understanding their predictive ability. Unlike the human visual system which is able to generalize robustly and learn with little supervision, DNNs normally require a massive amount of data to learn new concepts. In addition...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	153,405
2007.02374	Detail Preserved Point Cloud Completion via Separated Feature Aggregation	Point cloud shape completion is a challenging problem in 3D vision and robotics. Existing learning-based frameworks leverage encoder-decoder architectures to recover the complete shape from a highly encoded global feature vector. Though the global feature can approximately represent the overall shape of 3D objects, it ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	185,715
2306.05499	Prompt Injection attack against LLM-integrated Applications	Large Language Models (LLMs), renowned for their superior proficiency in language comprehension and generation, stimulate a vibrant ecosystem of applications around them. However, their extensive assimilation into various services introduces significant security risks. This study deconstructs the complexities and impli...	false	false	false	false	true	false	false	false	true	false	false	false	true	false	false	false	false	true	372,222
2404.02507	Lifelong Event Detection with Embedding Space Separation and Compaction	To mitigate forgetting, existing lifelong event detection methods typically maintain a memory module and replay the stored memory data during the learning of a new task. However, the simple combination of memory data and new-task samples can still result in substantial forgetting of previously acquired knowledge, which...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	443,884
2303.10826	Visual Prompt Multi-Modal Tracking	Visible-modal object tracking gives rise to a series of downstream multi-modal tracking tributaries. To inherit the powerful representations of the foundation model, a natural modus operandi for multi-modal tracking is full fine-tuning on the RGB-based parameters. Albeit effective, this manner is not optimal due to the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,594
2410.00285	Performance Evaluation of Deep Learning-based Quadrotor UAV Detection and Tracking Methods	Unmanned Aerial Vehicles (UAVs) are becoming more popular in various sectors, offering many benefits, yet introducing significant challenges to privacy and safety. This paper investigates state-of-the-art solutions for detecting and tracking quadrotor UAVs to address these concerns. Cutting-edge deep learning models, s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	493,301
2305.19502	Graph Entropy Minimization for Semi-supervised Node Classification	Node classifiers are required to comprehensively reduce prediction errors, training resources, and inference latency in the industry. However, most graph neural networks (GNN) concentrate only on one or two of them. The compromised aspects thus are the shortest boards on the bucket, hindering their practical deployment...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	369,556
2311.05992	Robust Adversarial Attacks Detection for Deep Learning based Relative Pose Estimation for Space Rendezvous	Research on developing deep learning techniques for autonomous spacecraft relative navigation challenges is continuously growing in recent years. Adopting those techniques offers enhanced performance. However, such approaches also introduce heightened apprehensions regarding the trustability and security of such deep l...	false	false	false	false	true	false	true	true	false	false	false	true	true	false	false	false	false	false	406,782
2010.09277	Modality-Pairing Learning for Brain Tumor Segmentation	Automatic brain tumor segmentation from multi-modality Magnetic Resonance Images (MRI) using deep learning methods plays an important role in assisting the diagnosis and treatment of brain tumor. However, previous methods mostly ignore the latent relationship among different modalities. In this work, we propose a novel...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	201,474
2402.06734	Corruption Robust Offline Reinforcement Learning with Human Feedback	We study data corruption robustness for reinforcement learning with human feedback (RLHF) in an offline setting. Given an offline dataset of pairs of trajectories along with feedback about human preferences, an $\varepsilon$-fraction of the pairs is corrupted (e.g., feedback flipped or trajectory features manipulated),...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	428,416
2305.14872	Timeseries-aware Uncertainty Wrappers for Uncertainty Quantification of Information-Fusion-Enhanced AI Models based on Machine Learning	As the use of Artificial Intelligence (AI) components in cyber-physical systems is becoming more common, the need for reliable system architectures arises. While data-driven models excel at perception tasks, model outcomes are usually not dependable enough for safety-critical applications. In this work,we present a tim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	367,304
1208.0291	Learning Expressive Linkage Rules using Genetic Programming	A central problem in data integration and data cleansing is to find entities in different data sources that describe the same real-world object. Many existing methods for identifying such entities rely on explicit linkage rules which specify the conditions that entities must fulfill in order to be considered to describ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	17,903
cs/0406008	Image compression by rectangular wavelet transform	We study image compression by a separable wavelet basis $\big\{\psi(2^{k_1}x-i)\psi(2^{k_2}y-j),$ $\phi(x-i)\psi(2^{k_2}y-j),$ $\psi(2^{k_1}(x-i)\phi(y-j),$ $\phi(x-i)\phi(y-i)\big\},$ where $k_1, k_2 \in \mathbb{Z}_+$; $i,j\in\mathbb{Z}$; and $\phi,\psi$ are elements of a standard biorthogonal wavelet basis in $L_2(\m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	538,230
2111.10747	MaIL: A Unified Mask-Image-Language Trimodal Network for Referring Image Segmentation	Referring image segmentation is a typical multi-modal task, which aims at generating a binary mask for referent described in given language expressions. Prior arts adopt a bimodal solution, taking images and languages as two modalities within an encoder-fusion-decoder pipeline. However, this pipeline is sub-optimal for...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	267,429
1912.09621	Understanding Deep Neural Network Predictions for Medical Imaging Applications	Computer-aided detection has been a research area attracting great interest in the past decade. Machine learning algorithms have been utilized extensively for this application as they provide a valuable second opinion to the doctors. Despite several machine learning models being available for medical imaging applicatio...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	158,116
2303.12118	Examining the Impact of Provenance-Enabled Media on Trust and Accuracy Perceptions	In recent years, industry leaders and researchers have proposed to use technical provenance standards to address visual misinformation spread through digitally altered media. By adding immutable and secure provenance information such as authorship and edit date to media metadata, social media users could potentially be...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	353,142
2402.08701	Primal-Dual Algorithms with Predictions for Online Bounded Allocation and Ad-Auctions Problems	Matching problems have been widely studied in the research community, especially Ad-Auctions with many applications ranging from network design to advertising. Following the various advancements in machine learning, one natural question is whether classical algorithms can benefit from machine learning and obtain better...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	429,201
0807.0204	Diversity Multiplexing Tradeoff of Asynchronous Cooperative Relay Networks	The assumption of nodes in a cooperative communication relay network operating in synchronous fashion is often unrealistic. In the present paper, we consider two different models of asynchronous operation in cooperative-diversity networks experiencing slow fading and examine the corresponding diversity-multiplexing tra...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,024

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