Split (1)

train · 203k rows

node_id int64 0 76.9k	label int64 0 39	text stringlengths 13 124k	neighbors listlengths 0 3.32k	mask stringclasses 4 values
18,378	16	Title: MMG-Ego4D: Multi-Modal Generalization in Egocentric Action Recognition Abstract: In this paper, we study a novel problem in egocentric action recognition, which we term as “Multimodal Generalization“ (MMG). MMG aims to study how systems can generalize when data from certain modalities is limited or even complete...	[]	Train
18,379	24	Title: A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction Abstract: Diffusion-based manifold learning methods have proven useful in representation learning and dimensionality reduction of modern high dimensional, high throughput, noisy datasets. Such datasets are especially present in fields l...	[ 35848 ]	Validation
18,380	16	Title: I2-SDF: Intrinsic Indoor Scene Reconstruction and Editing via Raytracing in Neural SDFs Abstract: In this work, we present I2-SDF, a new method for intrinsic indoor scene reconstruction and editing using differentiable Monte Carlo raytracing on neural signed distance fields (SDFs). Our holistic neural SDF-based ...	[ 30995, 17075, 13813 ]	Test
18,381	28	Title: Optimal Coordinated Transmit Beamforming for Networked Integrated Sensing and Communications Abstract: This paper studies a multi-antenna networked integrated sensing and communications (ISAC) system, in which a set of multi-antenna base stations (BSs) employ the coordinated transmit beamforming to serve multipl...	[]	Train
18,382	26	Title: Inferring comparative advantage via entropy maximization Abstract: We revise the procedure proposed by Balassa to infer comparative advantage, which is a standard tool, in Economics, to analyze specialization (of countries, regions, etc.). Balassa's approach compares the export of a product for each country with...	[]	Validation
18,383	26	Title: Inferring social networks from observed groups Abstract: Collecting social network data directly from network members can be challenging. One alternative involves inferring a social network from individuals' memberships in observed groups, such as teams or clubs. Through a series of simulations, I explore when w...	[]	Test
18,384	30	Title: A Preliminary Evaluation of ChatGPT for Zero-shot Dialogue Understanding Abstract: Zero-shot dialogue understanding aims to enable dialogue to track the user's needs without any training data, which has gained increasing attention. In this work, we investigate the understanding ability of ChatGPT for zero-shot d...	[ 12128, 33779, 2613, 31189, 12087, 35580, 1789 ]	Train
18,385	8	Title: Benchmarking and Security Considerations of Wi-Fi FTM for Ranging in IoT Devices Abstract: The IEEE 802.11mc standard introduces fine time measurement (Wi-Fi FTM) for highly-accurate synchronization between peers and round-trip time calculation (Wi-Fi RTT) for location estimation – typically with a precision of ...	[]	Validation
18,386	24	Title: Non-Parametric Outlier Synthesis Abstract: Out-of-distribution (OOD) detection is indispensable for safely deploying machine learning models in the wild. One of the key challenges is that models lack supervision signals from unknown data, and as a result, can produce overconfident predictions on OOD data. Recent...	[ 18945, 21649, 40451, 20437 ]	Validation
18,387	23	Title: An Empirical Study on Bugs Inside PyTorch: A Replication Study Abstract: Software systems are increasingly relying on deep learning components, due to their remarkable capability of identifying complex data patterns and powering intelligent behaviour. A core enabler of this change in software development is the ...	[]	Test
18,388	5	Title: Lessons Learned from a Performance Analysis and Optimization of a Multiscale Cellular Simulation Abstract: This work presents a comprehensive performance analysis and optimization of a multiscale agent-based cellular simulation. The optimizations applied are guided by detailed performance analysis and include me...	[]	Validation
18,389	23	Title: Reflections on Surrogate-Assisted Search-Based Testing: A Taxonomy and Two Replication Studies based on Industrial ADAS and Simulink Models Abstract: Surrogate-assisted search-based testing (SA-SBT) aims to reduce the computational time for testing compute-intensive systems. Surrogates enhance testing techniques...	[]	Train
18,390	16	Title: Artificial intelligence as a gateway to scientific discovery: Uncovering features in retinal fundus images Abstract: Purpose: Convolutional neural networks can be trained to detect various conditions or patient traits based on retinal fundus photographs, some of which, such as the patient sex, are invisible to t...	[]	Validation
18,391	16	Title: Detecting Everything in the Open World: Towards Universal Object Detection Abstract: In this paper, we formally address universal object detection, which aims to detect every scene and predict every category. The dependence on human annotations, the limited visual information, and the novel categories in the ope...	[ 36582, 6089, 26157, 31346, 8084, 30685, 22814 ]	Train
18,392	24	Title: Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis Abstract: Many machine learning algorithms require large numbers of labeled data to deliver state-of-the-art results. In applications such as medical diagnosis and fraud detection, though there is an abundance of unlabeled data,...	[ 11128, 34404, 13100, 39573 ]	Test
18,393	37	Title: Discovering Process Models that Support Desired Behavior and Avoid Undesired Behavior Abstract: Process discovery is one of the primary process mining tasks and starting point for process improvements using event data. Existing process discovery techniques aim to find process models that best describe the observ...	[]	Train
18,394	16	Title: Online Neural Path Guiding with Normalized Anisotropic Spherical Gaussians Abstract: The variance reduction speed of physically-based rendering is heavily affected by the adopted importance sampling technique. In this paper we propose a novel online framework to learn the spatial-varying density model with a sin...	[]	Test
18,395	24	Title: Decentralized Adversarial Training over Graphs Abstract: The vulnerability of machine learning models to adversarial attacks has been attracting considerable attention in recent years. Most existing studies focus on the behavior of stand-alone single-agent learners. In comparison, this work studies adversarial t...	[ 36442, 2557 ]	Train
18,396	8	Title: Photon: A Cross Platform P2P Data Transfer Application Abstract: Modern computing requires efficient and dependable data transport. Current solutions like Bluetooth, SMS (Short Message Service), and Email have their restrictions on efficiency, file size, compatibility, and cost. In order to facilitate direct com...	[]	Train
18,397	9	Title: Secret Sharing on Superconcentrator Abstract: Using information inequalities, we prove any unrestricted arithmetic circuits computing the shares of any $(t, n)$-threshold secret sharing scheme must satisfy some superconcentrator-like connection properties. In the reverse direction, we prove, when the underlying ...	[]	Validation
18,398	3	Title: Reconciling Governmental Use of Online Targeting With Democracy Abstract: The societal and epistemological implications of online targeted advertising have been scrutinized by AI ethicists, legal scholars, and policymakers alike. However, the government’s use of online targeting and its consequential socio-polit...	[]	Train
18,399	16	Title: Online Black-Box Confidence Estimation of Deep Neural Networks Abstract: Autonomous driving (AD) and advanced driver assistance systems (ADAS) increasingly utilize deep neural networks (DNNs) for improved perception or planning. Nevertheless, DNNs are quite brittle when the data distribution during inference dev...	[]	Train
18,400	28	Title: How much Training is Needed in Downlink Cell-Free mMIMO under LoS/NLoS channels? Abstract: The assumption that no LoS channels exist between wireless access points~(APs) and user equipments~(UEs) becomes questionable in the context of the recent developments in the direction of cell free massive multiple input m...	[]	Train
18,401	26	Title: Early warning signals for predicting cryptomarket vendor success using dark net forum networks Abstract: In this work we focus on identifying key players in dark net cryptomarkets. Law enforcement aims to disrupt criminal activity conducted through these markets by targeting key players vital to the market's exi...	[ 8561 ]	Train
18,402	15	Title: Adding Explicit Load-Acquire and Store-Release Instructions to the RISC-V ISA Abstract: Weak memory models allow for simplified hardware and increased performance in the memory hierarchy at the cost of increased software complexity. In weak memory models, explicit synchronization is needed to enforce ordering be...	[]	Test
18,403	2	Title: Trace models of concurrent valuation algebras Abstract: This paper introduces Concurrent Valuation Algebras (CVAs), a novel extension of ordered valuation algebras (OVAs). CVAs include two combine operators representing parallel and sequential products, adhering to a weak exchange law. This development offers th...	[]	Validation
18,404	24	Title: The first step is the hardest: Pitfalls of Representing and Tokenizing Temporal Data for Large Language Models Abstract: Large Language Models (LLMs) have demonstrated remarkable generalization across diverse tasks, leading individuals to increasingly use them as personal assistants and universal computing engin...	[ 10624, 36224, 37987, 42794, 16014, 23545, 32989 ]	Test
18,405	24	Title: Comparison of machine learning models applied on anonymized data with different techniques Abstract: Anonymization techniques based on obfuscating the quasi-identifiers by means of value generalization hierarchies are widely used to achieve preset levels of privacy. To prevent different types of attacks against ...	[]	Train
18,406	36	Title: Markov α-Potential Games: Equilibrium Approximation and Regret Analysis Abstract: This paper proposes a new framework to study multi-agent interaction in Markov games: Markov $\alpha$-potential games. Markov potential games are special cases of Markov $\alpha$-potential games, so are two important and practicall...	[ 41266 ]	Test
18,407	39	Title: Counting the minimum number of arcs in an oriented graph having weak diameter 2 Abstract: An oriented graph has weak diameter at most $d$ if every non-adjacent pair of vertices are connected by a directed $d$-path. The function $f_d(n)$ denotes the minimum number of arcs in an oriented graph on $n$ vertices havi...	[]	Train
18,408	10	Title: A Pilot Evaluation of ChatGPT and DALL-E 2 on Decision Making and Spatial Reasoning Abstract: We conduct a pilot study selectively evaluating the cognitive abilities (decision making and spatial reasoning) of two recently released generative transformer models, ChatGPT and DALL-E 2. Input prompts were constructe...	[ 11273, 35580 ]	Test
18,409	24	Title: CAMEL: Curvature-Augmented Manifold Embedding and Learning Abstract: A novel method, named Curvature-Augmented Manifold Embedding and Learning (CAMEL), is proposed for high dimensional data classification, dimension reduction, and visualization. CAMEL utilizes a topology metric defined on the Riemannian manifold...	[]	Train
18,410	28	Title: Beamforming in Wireless Coded-Caching Systems Abstract: Increased capacity in the access network poses capacity challenges on the transport network due to the aggregated traffic. However, there are spatial and time correlation in the user data demands that could potentially be utilized. To that end, we investiga...	[]	Train
18,411	23	Title: ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design Abstract: This paper presents prompt design techniques for software engineering, in the form of patterns, to solve common problems when using large language models (LLMs), such as ChatGPT to automate co...	[ 25227, 44173, 145, 32024, 25756, 34336, 33057, 43044, 45481, 8110, 43566, 11190, 14007, 13239, 7229, 21313, 33731, 18250, 43471, 44246, 28776, 1899, 19315, 28661, 16758, 35580 ]	Validation
18,412	2	Title: Variable Independence in Linear Real Arithmetic Abstract: Variable independence and decomposability are algorithmic techniques for simplifying logical formulas by tearing apart connections between free variables. These techniques were originally proposed to speed up query evaluation in constraint databases, in p...	[]	Train
18,413	10	Title: Scalable and Safe Remediation of Defective Actions in Self-Learning Conversational Systems Abstract: Off-Policy reinforcement learning has been the driving force for the state-of-the-art conversational AIs leading to more natural human-agent interactions and improving the user satisfaction for goal-oriented agen...	[]	Train
18,414	24	Title: Memory-Based Meta-Learning on Non-Stationary Distributions Abstract: Memory-based meta-learning is a technique for approximating Bayes-optimal predictors. Under fairly general conditions, minimizing sequential prediction error, measured by the log loss, leads to implicit meta-learning. The goal of this work is t...	[ 4822 ]	Train
18,415	27	Title: Stay on Track: A Frenet Wrapper to Overcome Off-road Trajectories in Vehicle Motion Prediction Abstract: Predicting the future motion of observed vehicles is a crucial enabler for safe autonomous driving. The field of motion prediction has seen large progress recently with State-of-the-Art (SotA) models achievin...	[ 8610, 18283 ]	Train
18,416	24	Title: Variational Boosted Soft Trees Abstract: Gradient boosting machines (GBMs) based on decision trees consistently demonstrate state-of-the-art results on regression and classification tasks with tabular data, often outperforming deep neural networks. However, these models do not provide well-calibrated predictive ...	[]	Validation
18,417	28	Title: 142 GHz Multipath Propagation Measurements and Path Loss Channel Modeling in Factory Buildings Abstract: This paper presents sub-Terahertz (THz) radio propagation measurements at 142 GHz conducted in four factories with various layouts and facilities to explore sub-THz wireless channels for smart factories in 6G...	[ 21352 ]	Train
18,418	30	Title: TADA: Task-Agnostic Dialect Adapters for English Abstract: Large Language Models, the dominant starting point for Natural Language Processing (NLP) applications, fail at a higher rate for speakers of English dialects other than Standard American English (SAE). Prior work addresses this using task-specific data o...	[]	Train
18,419	6	Title: SeeChart: Enabling Accessible Visualizations Through Interactive Natural Language Interface For People with Visual Impairments Abstract: Web-based data visualizations have become very popular for exploring data and communicating insights. Newspapers, journals, and reports regularly publish visualizations to tell...	[]	Test
18,420	16	Title: Top-Down Beats Bottom-Up in 3D Instance Segmentation Abstract: Most 3D instance segmentation methods exploit a bottom-up strategy, typically including resource-exhaustive post-processing. For point grouping, bottom-up methods rely on prior assumptions about the objects in the form of hyperparameters, which are d...	[ 7569, 42404 ]	Train
18,421	16	Title: Optimizing ViViT Training: Time and Memory Reduction for Action Recognition Abstract: In this paper, we address the challenges posed by the substantial training time and memory consumption associated with video transformers, focusing on the ViViT (Video Vision Transformer) model, in particular the Factorised Enc...	[ 20169 ]	Test
18,422	16	Title: Are Local Features All You Need for Cross-Domain Visual Place Recognition? Abstract: Visual Place Recognition is a task that aims to predict the coordinates of an image (called query) based solely on visual clues. Most commonly, a retrieval approach is adopted, where the query is matched to the most similar imag...	[ 30875 ]	Train
18,423	16	Title: A Graph Neural Network Approach for Temporal Mesh Blending and Correspondence Abstract: We have proposed a self-supervised deep learning framework for solving the mesh blending problem in scenarios where the meshes are not in correspondence. To solve this problem, we have developed Red-Blue MPNN, a novel graph n...	[]	Train
18,424	5	Title: Shared memory parallelism in Modern C++ and HPX Abstract: nan	[ 39033, 35562 ]	Validation
18,425	16	Title: Estimating friction coefficient using generative modelling Abstract: It is common to utilise dynamic models to measure the tyre-road friction in real-time. Alternatively, predictive approaches estimate the tyre-road friction by identifying the environmental factors affecting it. This work aims to formulate the p...	[]	Validation
18,426	8	Title: On Blowback Traffic on the Internet Abstract: This paper considers the phenomenon where a single probe to a target generates multiple, sometimes numerous, packets in response -- which we term"blowback". Understanding blowback is important because attackers can leverage it to launch amplified denial of service at...	[]	Validation
18,427	24	Title: Plan4MC: Skill Reinforcement Learning and Planning for Open-World Minecraft Tasks Abstract: We study building a multi-task agent in Minecraft. Without human demonstrations, solving long-horizon tasks in this open-ended environment with reinforcement learning (RL) is extremely sample inefficient. To tackle the ch...	[ 22816, 14991, 44687, 32820, 39669, 21782, 18459, 8157 ]	Train
18,428	30	Title: A Function Interpretation Benchmark for Evaluating Interpretability Methods Abstract: Labeling neural network submodules with human-legible descriptions is useful for many downstream tasks: such descriptions can surface failures, guide interventions, and perhaps even explain important model behaviors. To date, m...	[ 22252, 38834, 4434, 43641, 9403 ]	Train
18,429	16	Title: Adaptive Data-Free Quantization Abstract: Data-free quantization (DFQ) recovers the performance of quantized network (Q) without the original data, but generates the fake sample via a generator (G) by learning from full-precision network (P), which, however, is totally independent of Q, overlooking the adaptabil...	[ 4174, 574, 16767 ]	Train
18,430	24	Title: Active Deep Learning Guided by Efficient Gaussian Process Surrogates Abstract: The success of active learning relies on the exploration of the underlying data-generating distributions, populating sparsely labeled data areas, and exploitation of the information about the task gained by the baseline (neural networ...	[]	Test
18,431	16	Title: POCE: Pose-Controllable Expression Editing Abstract: Facial expression editing has attracted increasing attention with the advance of deep neural networks in recent years. However, most existing methods suffer from compromised editing fidelity and limited usability as they either ignore pose variations (unrealis...	[]	Test
18,432	30	Title: Conversational Agents and Children: Let Children Learn Abstract: Using online information discovery as a case study, in this position paper we discuss the need to design, develop, and deploy (conversational) agents that can -- non-intrusively -- guide children in their quest for online resources rather than simp...	[]	Train
18,433	16	Title: CBA: Contextual Background Attack Against Optical Aerial Detection in the Physical World Abstract: Patch-based physical attacks have increasingly aroused concerns. However, most existing methods focus on obscuring targets captured on the ground, and some of these methods are simply extended to deceive aerial det...	[ 6987, 18347 ]	Train
18,434	24	Title: Mode Combinability: Exploring Convex Combinations of Permutation Aligned Models Abstract: We explore element-wise convex combinations of two permutation-aligned neural network parameter vectors $\Theta_A$ and $\Theta_B$ of size $d$. We conduct extensive experiments by examining various distributions of such mode...	[ 5815 ]	Validation
18,435	27	Title: Design of Mobile Manipulator for Fire Extinguisher Testing. Part II: Design and Simulation Abstract: . All flames are extinguished as early as possible, or fire services have to deal with major conflagrations. This leads to the fact that the quality of fire extinguishers has become a very sensitive and important...	[]	Test
18,436	24	Title: Deep Learning for Energy Time-Series Analysis and Forecasting Abstract: Energy time-series analysis describes the process of analyzing past energy observations and possibly external factors so as to predict the future. Different tasks are involved in the general field of energy time-series analysis and forecasti...	[]	Train
18,437	10	Title: Autocodificadores Variacionales (VAE) Fundamentos Teóricos y Aplicaciones Abstract: VAEs are probabilistic graphical models based on neural networks that allow the coding of input data in a latent space formed by simpler probability distributions and the reconstruction, based on such latent variables, of the sou...	[]	Train
18,438	27	Title: Implementing BDI Continual Temporal Planning for Robotic Agents Abstract: Making autonomous agents effective in real-life applications requires the ability to decide at run-time and a high degree of adaptability to unpredictable and uncontrollable events. Reacting to events is still a fundamental ability for an ...	[]	Train
18,439	30	Title: Unifying Structure Reasoning and Language Model Pre-training for Complex Reasoning Abstract: Recent pre-trained language models (PLMs) equipped with foundation reasoning skills have shown remarkable performance on downstream complex tasks. However, the significant structure reasoning skill has been rarely studie...	[ 45131, 15293, 31215 ]	Train
18,440	6	Title: Online Poker and Rummy - Games of Skill or Chance? Abstract: The paper aims to investigate the degree of cognitive skills required for success in online versions of the popular card game rummy and poker. The study focuses on analyzing the impact of experience and learnable skills on success in the online card ga...	[]	Validation
18,441	30	Title: Extractive Summarization via ChatGPT for Faithful Summary Generation Abstract: Extractive summarization is a crucial task in natural language processing that aims to condense long documents into shorter versions by directly extracting sentences. The recent introduction of ChatGPT has attracted significant intere...	[ 19200, 28151, 17349, 17989, 6535, 38253, 7055, 12087, 12601, 6075, 8286 ]	Train
18,442	13	Title: Competitive plasticity to reduce the energetic costs of learning Abstract: The brain is not only constrained by energy needed to fuel computation, but it is also constrained by energy needed to form memories. Experiments have shown that learning simple conditioning tasks already carries a significant metabolic c...	[ 16505 ]	Test
18,443	4	Title: Mitigating Speculation-based Attacks through Configurable Hardware/Software Co-design Abstract: New speculation-based attacks that affect large numbers of modern systems are disclosed regularly. Currently, CPU vendors regularly fall back to heavy-handed mitigations like using barriers or enforcing strict program...	[ 5351 ]	Validation
18,444	16	Title: LiT Tuned Models for Efficient Species Detection Abstract: Recent advances in training vision-language models have demonstrated unprecedented robustness and transfer learning effectiveness; however, standard computer vision datasets are image-only, and therefore not well adapted to such training methods. Our pap...	[]	Train
18,445	16	Title: FIT: Frequency-based Image Translation for Domain Adaptive Object Detection Abstract: Domain adaptive object detection (DAOD) aims to adapt the detector from a labelled source domain to an unlabelled target domain. In recent years, DAOD has attracted massive attention since it can alleviate performance degradati...	[]	Train
18,446	27	Title: The Director: A Composable Behaviour System with Soft Transitions Abstract: Software frameworks for behaviour are critical in robotics as they enable the correct and efficient execution of functions. While modern behaviour systems have improved their composability, they do not focus on smooth transitions and oft...	[]	Validation
18,447	16	Title: SATR: Zero-Shot Semantic Segmentation of 3D Shapes Abstract: We explore the task of zero-shot semantic segmentation of 3D shapes by using large-scale off-the-shelf 2D image recognition models. Surprisingly, we find that modern zero-shot 2D object detectors are better suited for this task than contemporary text/i...	[ 18214, 16524, 22222, 5583, 23152, 33969, 33875, 17046, 18267 ]	Validation
18,448	8	Title: How Can AI be Distributed in the Computing Continuum? Introducing the Neural Pub/Sub Paradigm Abstract: This paper proposes the neural publish/subscribe paradigm, a novel approach to orchestrating AI workflows in large-scale distributed AI systems in the computing continuum. Traditional centralized broker method...	[ 1441 ]	Train
18,449	30	Title: SpanRE: Entities and Overlapping Relations Extraction Based on Spans and Entity Attention Abstract: Extracting entities and relations is an essential task of information extraction. Triplets extracted from a sentence might overlap with each other. Previous methods either did not address the overlapping issues or...	[]	Test
18,450	32	Title: $\texttt{ChisholmD.wl}$- Automated rational approximant for bi-variate series Abstract: The Chisholm rational approximant is a natural generalization to two variables of the well-known single variable Pad\'e approximant, and has the advantage of reducing to the latter when one of the variables is set equals to 0...	[]	Train
18,451	34	Title: Better Diameter Algorithms for Bounded VC-dimension Graphs and Geometric Intersection Graphs Abstract: We develop a framework for algorithms finding diameter in graphs of bounded distance Vapnik-Chervonenkis dimension, in (parametrized) sub-quadratic time complexity. The class of bounded distance VC-dimension gr...	[]	Test
18,452	16	Title: Predicting Cardiovascular Disease Risk using Photoplethysmography and Deep Learning Abstract: Cardiovascular diseases (CVDs) are responsible for a large proportion of premature deaths in low- and middle-income countries. Early CVD detection and intervention is critical in these populations, yet many existing CVD...	[ 13766 ]	Train
18,453	24	Title: Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale Abstract: In this paper, we address the following problem: Given an offline demonstration dataset from an imperfect expert, what is the best way to leverage it to bootstrap online learning performance in MDPs. We first propose an Informed P...	[ 15201 ]	Train
18,454	28	Title: Distributed Signal Processing for Out-of-System Interference Suppression in Cell-Free Massive MIMO Abstract: Cell-free massive multiple-input-multiple-output (CF-mMIMO) is a next-generation wireless access technology that offers superior coverage and spectral efficiency compared to conventional MIMO. With many f...	[]	Validation
18,455	1	Title: Video-to-Music Recommendation Using Temporal Alignment of Segments Abstract: We study cross-modal recommendation of musictracks to be used as soundtracks for videos. This problem is known as the music supervision task. We build on a self-supervised system that learns a content association between music and video...	[]	Train
18,456	24	Title: AdaSelection: Accelerating Deep Learning Training through Data Subsampling Abstract: In this paper, we introduce AdaSelection, an adaptive sub-sampling method to identify the most informative sub-samples within each minibatch to speed up the training of large-scale deep learning models without sacrificing model ...	[]	Validation
18,457	37	Title: NoSQL Schema Design for Time-Dependent Workloads Abstract: In this paper, we propose a schema optimization method for time-dependent workloads for NoSQL databases. In our proposed method, we migrate schema according to changing workloads, and the estimated cost of execution and migration are formulated and minim...	[]	Train
18,458	16	Title: BSDM: Background Suppression Diffusion Model for Hyperspectral Anomaly Detection Abstract: Hyperspectral anomaly detection (HAD) is widely used in Earth observation and deep space exploration. A major challenge for HAD is the complex background of the input hyperspectral images (HSIs), resulting in anomalies con...	[]	Test
18,459	10	Title: Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory Abstract: The captivating realm of Minecraft has attracted substantial research interest in recent years, serving as a rich platform for developing intelligent agents capabl...	[ 22816, 9379, 32036, 16837, 33477, 28668, 14991, 17328, 39669, 44759, 1528, 634, 18427, 13564, 18621, 3967 ]	Train
18,460	10	Title: For Better or Worse: The Impact of Counterfactual Explanations' Directionality on User Behavior in xAI Abstract: Counterfactual explanations (CFEs) are a popular approach in explainable artificial intelligence (xAI), highlighting changes to input data necessary for altering a model's output. A CFE can either des...	[]	Train
18,461	4	Title: Secure Computation over Encrypted Databases Abstract: Sensitive applications running on the cloud often require data to be stored in an encrypted domain. To run data mining algorithms on such data, partially homomorphic encryption schemes (allowing certain operations in the ciphertext domain) have been devised. ...	[]	Train
18,462	22	Title: Differentiable Programming: Efficient Smoothing of Control-Flow-Induced Discontinuities Abstract: We want to obtain derivatives in discontinuous program code, where default Algorithmic Differentiation may not perform well. Specifically, we consider discontinuities induced by control flow statements, where meanin...	[ 16231 ]	Train
18,463	16	Title: Cross-supervised Dual Classifiers for Semi-supervised Medical Image Segmentation Abstract: Semi-supervised medical image segmentation offers a promising solution for large-scale medical image analysis by significantly reducing the annotation burden while achieving comparable performance. Employing this method ex...	[]	Test
18,464	16	Title: Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly Detection Abstract: Video anomaly detection under weak supervision is challenging due to the absence of frame-level annotations during the training phase. Previous work has employed graph convolution networks or self-attention mechanis...	[ 13851 ]	Test
18,465	5	Title: Fault Awareness in the MPI 4.0 Session Model Abstract: MPI version 4.0 introduces new functionalities like the Session model but still lacks fault management mechanisms. Past efforts produced tools and MPI standard extensions to manage fault presence, including User Level Fault Mitigation (ULFM). These measures ...	[]	Train
18,466	16	Title: Revisiting Deformable Convolution for Depth Completion Abstract: Depth completion, which aims to generate high-quality dense depth maps from sparse depth maps, has attracted increasing attention in recent years. Previous work usually employs RGB images as guidance, and introduces iterative spatial propagation to...	[]	Validation
18,467	28	Title: (α, β)-Leakage: A Unified Privacy Leakage Measure Abstract: We introduce a family of information leakage measures called maximal $(\alpha,\beta)$-leakage, parameterized by non-negative real numbers $\alpha$ and $\beta$. The measure is formalized via an operational definition involving an adversary guessing an un...	[]	Test
18,468	24	Title: Hierarchical Optimization-Derived Learning Abstract: In recent years, by utilizing optimization techniques to formulate the propagation of deep model, a variety of so-called Optimization-Derived Learning (ODL) approaches have been proposed to address diverse learning and vision tasks. Although having achieved re...	[]	Train
18,469	24	Title: Privacy Loss of Noisy Stochastic Gradient Descent Might Converge Even for Non-Convex Losses Abstract: The Noisy-SGD algorithm is widely used for privately training machine learning models. Traditional privacy analyses of this algorithm assume that the internal state is publicly revealed, resulting in privacy los...	[]	Train
18,470	16	Title: Segment Any Anomaly without Training via Hybrid Prompt Regularization Abstract: We present a novel framework, i.e., Segment Any Anomaly + (SAA+), for zero-shot anomaly segmentation with hybrid prompt regularization to improve the adaptability of modern foundation models. Existing anomaly segmentation models typi...	[ 12704, 33922, 37029, 25701, 35263, 1228, 41517, 3217, 39761, 18360, 1144, 33049, 20955, 1151 ]	Train
18,471	16	Title: Multi-Level Memory-Augmented Appearance-Motion Correspondence Framework for Video Anomaly Detection Abstract: Frame prediction based on AutoEncoder plays a significant role in unsupervised video anomaly detection. Ideally, the models trained on the normal data could generate larger prediction errors of anomalies...	[]	Validation
18,472	30	Title: Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval Abstract: Recently multi-lingual pre-trained language models (PLM) such as mBERT and XLM-R have achieved impressive strides in cross-lingual dense retrieval. Despite its successes, they are general-purpose PLM while the multilingual P...	[]	Train
18,473	24	Title: Learning high-dimensional causal effect Abstract: The scarcity of high-dimensional causal inference datasets restricts the exploration of complex deep models. In this work, we propose a method to generate a synthetic causal dataset that is high-dimensional. The synthetic data simulates a causal effect using the ...	[]	Train
18,474	16	Title: Unsupervised Adaptation of Polyp Segmentation Models via Coarse-to-Fine Self-Supervision Abstract: nan	[]	Train
18,475	6	Title: Science Communications for Explainable Artificial Intelligence Abstract: Artificial Intelligence (AI) has a communication problem. XAI methods have been used to make AI more understandable and helped resolve some of the transparency issues that inhibit AI's broader usability. However, user evaluation studies rev...	[]	Train
18,476	30	Title: Donkii: Can Annotation Error Detection Methods Find Errors in Instruction-Tuning Datasets? Abstract: Instruction-tuning has become an integral part of training pipelines for Large Language Models (LLMs) and has been shown to yield strong performance gains. In an orthogonal line of research, Annotation Error Dete...	[ 33220, 13700, 11717, 18764 ]	Train
18,477	16	Title: One-Pot Multi-Frame Denoising Abstract: The performance of learning-based denoising largely depends on clean supervision. However, it is difficult to obtain clean images in many scenes. On the contrary, the capture of multiple noisy frames for the same field of view is available and often natural in real life. T...	[]	Train

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