id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2411.13496 | Advancing Heatwave Forecasting via Distribution Informed-Graph Neural
Networks (DI-GNNs): Integrating Extreme Value Theory with GNNs | [
"cs.LG",
"physics.ao-ph",
"physics.soc-ph"
] | Heatwaves, prolonged periods of extreme heat, have intensified in frequency and severity due to climate change, posing substantial risks to public health, ecosystems, and infrastructure. Despite advancements in Machine Learning (ML) modeling, accurate heatwave forecasting at weather scales (1--15 days) remains challeng... | {
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2411.13503 | VBench++: Comprehensive and Versatile Benchmark Suite for Video
Generative Models | [
"cs.CV"
] | Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable for two reasons: 1) Existing metrics do not fully align with human perceptions; 2) An ideal evaluation system should provide insights to in... | {
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2411.13504 | Disentangling Memory and Reasoning Ability in Large Language Models | [
"cs.CL"
] | Large Language Models (LLMs) have demonstrated strong performance in handling complex tasks requiring both extensive knowledge and reasoning abilities. However, the existing LLM inference pipeline operates as an opaque process without explicit separation between knowledge retrieval and reasoning steps, making the model... | {
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2411.13506 | Bezier Reachable Polytopes: Efficient Certificates for Robust Motion
Planning with Layered Architectures | [
"cs.RO",
"cs.SY",
"eess.SY"
] | Control architectures are often implemented in a layered fashion, combining independently designed blocks to achieve complex tasks. Providing guarantees for such hierarchical frameworks requires considering the capabilities and limitations of each layer and their interconnections at design time. To address this holisti... | {
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2411.13507 | Dynamically Feasible Path Planning in Cluttered Environments via
Reachable Bezier Polytopes | [
"cs.RO",
"cs.SY",
"eess.SY"
] | The deployment of robotic systems in real world environments requires the ability to quickly produce paths through cluttered, non-convex spaces. These planned trajectories must be both kinematically feasible (i.e., collision free) and dynamically feasible (i.e., satisfy the underlying system dynamics), necessitating a ... | {
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2411.13509 | Degenerate quantum erasure decoding | [
"quant-ph",
"cs.IT",
"math.IT"
] | Erasures are the primary type of errors in physical systems dominated by leakage errors. While quantum error correction (QEC) using stabilizer codes can combat these error, the question of achieving near-capacity performance with explicit codes and efficient decoders remains a challenge. Quantum decoding is a classical... | {
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2411.13512 | Dyson Brownian motion and random matrix dynamics of weight matrices
during learning | [
"cond-mat.dis-nn",
"cs.LG",
"hep-lat"
] | During training, weight matrices in machine learning architectures are updated using stochastic gradient descent or variations thereof. In this contribution we employ concepts of random matrix theory to analyse the resulting stochastic matrix dynamics. We first demonstrate that the dynamics can generically be described... | {
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2411.13513 | Procurement Auctions via Approximately Optimal Submodular Optimization | [
"cs.GT",
"cs.DS",
"cs.LG"
] | We study procurement auctions, where an auctioneer seeks to acquire services from strategic sellers with private costs. The quality of services is measured by a submodular function known to the auctioneer. Our goal is to design computationally efficient procurement auctions that (approximately) maximize the difference ... | {
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2411.13517 | Understanding the Personal Networks of People Experiencing Homelessness
in King County, WA with aggregate Relational Data | [
"cs.SI",
"physics.soc-ph"
] | The social networks of people experiencing homelessness are an understudied but vital aspect of their lives, offering access to information, support, and safety. In 2023, the U.S. Department of Housing and Urban Development reported 653,100 people experiencing homelessness on any given night -- a 23% rise since 2022, t... | {
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2411.13518 | Advancing Complex Medical Communication in Arabic with Sporo AraSum:
Surpassing Existing Large Language Models | [
"cs.CL",
"cs.AI"
] | The increasing demand for multilingual capabilities in healthcare underscores the need for AI models adept at processing diverse languages, particularly in clinical documentation and decision-making. Arabic, with its complex morphology, syntax, and diglossia, poses unique challenges for natural language processing (NLP... | {
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2411.13520 | Quantum Attention for Vision Transformers in High Energy Physics | [
"quant-ph",
"cs.LG",
"hep-ex",
"hep-ph"
] | We present a novel hybrid quantum-classical vision transformer architecture incorporating quantum orthogonal neural networks (QONNs) to enhance performance and computational efficiency in high-energy physics applications. Building on advancements in quantum vision transformers, our approach addresses limitations of pri... | {
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2411.13525 | Geometric Algebra Planes: Convex Implicit Neural Volumes | [
"cs.CV"
] | Volume parameterizations abound in recent literature, from the classic voxel grid to the implicit neural representation and everything in between. While implicit representations have shown impressive capacity and better memory efficiency compared to voxel grids, to date they require training via nonconvex optimization.... | {
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2411.13528 | Entropy Bootstrapping for Weakly Supervised Nuclei Detection | [
"cs.CV",
"cs.AI"
] | Microscopy structure segmentation, such as detecting cells or nuclei, generally requires a human to draw a ground truth contour around each instance. Weakly supervised approaches (e.g. consisting of only single point labels) have the potential to reduce this workload significantly. Our approach uses individual point la... | {
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2411.13534 | Predictive Insights into LGBTQ+ Minority Stress: A Transductive
Exploration of Social Media Discourse | [
"cs.CL"
] | Individuals who identify as sexual and gender minorities, including lesbian, gay, bisexual, transgender, queer, and others (LGBTQ+) are more likely to experience poorer health than their heterosexual and cisgender counterparts. One primary source that drives these health disparities is minority stress (i.e., chronic an... | {
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2411.13535 | Comparative Analysis of Machine Learning and Deep Learning Models for
Classifying Squamous Epithelial Cells of the Cervix | [
"eess.IV",
"cs.CV"
] | The cervix is the narrow end of the uterus that connects to the vagina in the female reproductive system. Abnormal cell growth in the squamous epithelial lining of the cervix leads to cervical cancer in females. A Pap smear is a diagnostic procedure used to detect cervical cancer by gently collecting cells from the sur... | {
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2411.13536 | Identity Preserving 3D Head Stylization with Multiview Score
Distillation | [
"cs.CV",
"cs.AI",
"cs.GR",
"cs.LG",
"cs.MM"
] | 3D head stylization transforms realistic facial features into artistic representations, enhancing user engagement across gaming and virtual reality applications. While 3D-aware generators have made significant advancements, many 3D stylization methods primarily provide near-frontal views and struggle to preserve the un... | {
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2411.13537 | Metacognition for Unknown Situations and Environments (MUSE) | [
"cs.LG",
"cs.AI"
] | Metacognition--the awareness and regulation of one's cognitive processes--is central to human adaptability in unknown situations. In contrast, current autonomous agents often struggle in novel environments due to their limited capacity for adaptation. We hypothesize that metacognition is a critical missing ingredient i... | {
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2411.13543 | BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games | [
"cs.AI"
] | Large Language Models (LLMs) and Vision Language Models (VLMs) possess extensive knowledge and exhibit promising reasoning abilities; however, they still struggle to perform well in complex, dynamic environments. Real-world tasks require handling intricate interactions, advanced spatial reasoning, long-term planning, a... | {
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2411.13544 | DIS-Mine: Instance Segmentation for Disaster-Awareness in Poor-Light
Condition in Underground Mines | [
"cs.CV"
] | Detecting disasters in underground mining, such as explosions and structural damage, has been a persistent challenge over the years. This problem is compounded for first responders, who often have no clear information about the extent or nature of the damage within the mine. The poor-light or even total darkness inside... | {
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2411.13545 | Pushing the Limits of Sparsity: A Bag of Tricks for Extreme Pruning | [
"cs.CV"
] | Pruning of deep neural networks has been an effective technique for reducing model size while preserving most of the performance of dense networks, crucial for deploying models on memory and power-constrained devices. While recent sparse learning methods have shown promising performance up to moderate sparsity levels s... | {
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2411.13546 | Promoting User Data Autonomy During the Dissolution of a Monopolistic
Firm | [
"cs.LG"
] | The deployment of AI in consumer products is currently focused on the use of so-called foundation models, large neural networks pre-trained on massive corpora of digital records. This emphasis on scaling up datasets and pre-training computation raises the risk of further consolidating the industry, and enabling monopol... | {
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2411.13547 | SpecTool: A Benchmark for Characterizing Errors in Tool-Use LLMs | [
"cs.SE",
"cs.AI"
] | Evaluating the output of Large Language Models (LLMs) is one of the most critical aspects of building a performant compound AI system. Since the output from LLMs propagate to downstream steps, identifying LLM errors is crucial to system performance. A common task for LLMs in AI systems is tool use. While there are seve... | {
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2411.13548 | HF-Diff: High-Frequency Perceptual Loss and Distribution Matching for
One-Step Diffusion-Based Image Super-Resolution | [
"cs.CV",
"cs.LG"
] | Although recent diffusion-based single-step super-resolution methods achieve better performance as compared to SinSR, they are computationally complex. To improve the performance of SinSR, we investigate preserving the high-frequency detail features during super-resolution (SR) because the downgraded images lack detail... | {
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2411.13549 | Generating 3D-Consistent Videos from Unposed Internet Photos | [
"cs.CV"
] | We address the problem of generating videos from unposed internet photos. A handful of input images serve as keyframes, and our model interpolates between them to simulate a path moving between the cameras. Given random images, a model's ability to capture underlying geometry, recognize scene identity, and relate frame... | {
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2411.13550 | Find Any Part in 3D | [
"cs.CV"
] | We study open-world part segmentation in 3D: segmenting any part in any object based on any text query. Prior methods are limited in object categories and part vocabularies. Recent advances in AI have demonstrated effective open-world recognition capabilities in 2D. Inspired by this progress, we propose an open-world, ... | {
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2411.13552 | REDUCIO! Generating 1024$\times$1024 Video within 16 Seconds using
Extremely Compressed Motion Latents | [
"cs.CV"
] | Commercial video generation models have exhibited realistic, high-fidelity results but are still restricted to limited access. One crucial obstacle for large-scale applications is the expensive training and inference cost. In this paper, we argue that videos contain much more redundant information than images, thus can... | {
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2411.13553 | AI-generated Image Detection: Passive or Watermark? | [
"cs.CR",
"cs.CV",
"cs.LG"
] | While text-to-image models offer numerous benefits, they also pose significant societal risks. Detecting AI-generated images is crucial for mitigating these risks. Detection methods can be broadly categorized into passive and watermark-based approaches: passive detectors rely on artifacts present in AI-generated images... | {
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2411.13559 | Composing Ensembles of Instrument-Model Pairs for Optimizing
Profitability in Algorithmic Trading | [
"q-fin.TR",
"cs.AI",
"cs.LG"
] | Financial markets are nonlinear with complexity, where different types of assets are traded between buyers and sellers, each having a view to maximize their Return on Investment (ROI). Forecasting market trends is a challenging task since various factors like stock-specific news, company profiles, public sentiments, an... | {
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2411.13560 | AMSnet-KG: A Netlist Dataset for LLM-based AMS Circuit Auto-Design Using
Knowledge Graph RAG | [
"cs.AI",
"cs.AR",
"cs.ET",
"eess.SP"
] | High-performance analog and mixed-signal (AMS) circuits are mainly full-custom designed, which is time-consuming and labor-intensive. A significant portion of the effort is experience-driven, which makes the automation of AMS circuit design a formidable challenge. Large language models (LLMs) have emerged as powerful t... | {
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2411.13562 | The Role of AI in Financial Forecasting: ChatGPT's Potential and
Challenges | [
"q-fin.ST",
"cs.AI",
"cs.CY"
] | The outlook for the future of artificial intelligence (AI) in the financial sector, especially in financial forecasting, the challenges and implications. The dynamics of AI technology, including deep learning, reinforcement learning, and integration with blockchAIn and the Internet of Things, also highlight the continu... | {
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2411.13564 | A Random Forest approach to detect and identify Unlawful Insider Trading | [
"q-fin.ST",
"cs.LG",
"q-fin.RM",
"q-fin.TR"
] | According to The Exchange Act, 1934 unlawful insider trading is the abuse of access to privileged corporate information. While a blurred line between "routine" the "opportunistic" insider trading exists, detection of strategies that insiders mold to maneuver fair market prices to their advantage is an uphill battle for... | {
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2411.13566 | Integrated Water Resource Management in the Segura Hydrographic Basin:
An Artificial Intelligence Approach | [
"cs.AI"
] | Managing resources effectively in uncertain demand, variable availability, and complex governance policies is a significant challenge. This paper presents a paradigmatic framework for addressing these issues in water management scenarios by integrating advanced physical modelling, remote sensing techniques, and Artific... | {
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2411.13571 | A low-rank balanced truncation approach for large-scale RLCk model order
reduction based on extended Krylov subspace and a frequency-aware convergence
criterion | [
"math.NA",
"cs.AR",
"cs.CE",
"cs.NA"
] | Model order reduction (MOR) is essential in integrated circuit design, particularly when dealing with large-scale electromagnetic models extracted from complex designs. The numerous passive elements introduced in these models pose significant challenges in the simulation process. MOR methods based on balanced truncatio... | {
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2411.13572 | Public Health Advocacy Dataset: A Dataset of Tobacco Usage Videos from
Social Media | [
"cs.CV"
] | The Public Health Advocacy Dataset (PHAD) is a comprehensive collection of 5,730 videos related to tobacco products sourced from social media platforms like TikTok and YouTube. This dataset encompasses 4.3 million frames and includes detailed metadata such as user engagement metrics, video descriptions, and search keyw... | {
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2411.13573 | Higher-Order Spectral Element Methods for Electromagnetic Modeling of
Complex Anisotropic Waveguides | [
"math.NA",
"cs.CE",
"cs.NA"
] | This research thesis presents a novel higher-order spectral element method (SEM) formulated in cylindrical coordinates for analyzing electromagnetic fields in waveguides filled with complex anisotropic media. In this study, we consider a large class of cylindrical waveguides: radially-bounded and radially-unbounded dom... | {
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2411.13577 | WavChat: A Survey of Spoken Dialogue Models | [
"eess.AS",
"cs.CL",
"cs.LG",
"cs.MM",
"cs.SD"
] | Recent advancements in spoken dialogue models, exemplified by systems like GPT-4o, have captured significant attention in the speech domain. Compared to traditional three-tier cascaded spoken dialogue models that comprise speech recognition (ASR), large language models (LLMs), and text-to-speech (TTS), modern spoken di... | {
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2411.13578 | COOD: Concept-based Zero-shot OOD Detection | [
"cs.CV",
"cs.AI",
"cs.LG"
] | How can models effectively detect out-of-distribution (OOD) samples in complex, multi-label settings without extensive retraining? Existing OOD detection methods struggle to capture the intricate semantic relationships and label co-occurrences inherent in multi-label settings, often requiring large amounts of training ... | {
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2411.13581 | Browser Extension for Fake URL Detection | [
"cs.CR",
"cs.CE",
"cs.CY",
"cs.LG"
] | In recent years, Cyber attacks have increased in number, and with them, the intensity of the attacks and their potential to damage the user have also increased significantly. In an ever-advancing world, users find it difficult to keep up with the latest developments in technology, which can leave them vulnerable to att... | {
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2411.13582 | Deep Feature Response Discriminative Calibration | [
"cs.CV"
] | Deep neural networks (DNNs) have numerous applications across various domains. Several optimization techniques, such as ResNet and SENet, have been proposed to improve model accuracy. These techniques improve the model performance by adjusting or calibrating feature responses according to a uniform standard. However, t... | {
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2411.13583 | Enhanced FIWARE-Based Architecture for Cyberphysical Systems With Tiny
Machine Learning and Machine Learning Operations: A Case Study on Urban
Mobility Systems | [
"cs.CR",
"cs.AI",
"cs.DC",
"cs.NI"
] | The rise of AI and the Internet of Things is accelerating the digital transformation of society. Mobility computing presents specific barriers due to its real-time requirements, decentralization, and connectivity through wireless networks. New research on edge computing and tiny machine learning (tinyML) explores the e... | {
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2411.13584 | AddrLLM: Address Rewriting via Large Language Model on Nationwide
Logistics Data | [
"cs.CL",
"cs.AI"
] | Textual description of a physical location, commonly known as an address, plays an important role in location-based services(LBS) such as on-demand delivery and navigation. However, the prevalence of abnormal addresses, those containing inaccuracies that fail to pinpoint a location, have led to significant costs. Addre... | {
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2411.13585 | Artificial Intelligence in Cybersecurity: Building Resilient Cyber
Diplomacy Frameworks | [
"cs.CR",
"cs.AI",
"cs.CY"
] | This paper explores how automation and artificial intelligence (AI) are transforming U.S. cyber diplomacy. Leveraging these technologies helps the U.S. manage the complexity and urgency of cyber diplomacy, improving decision-making, efficiency, and security. As global inter connectivity grows, cyber diplomacy, managing... | {
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2411.13586 | Advance Detection Of Bull And Bear Phases In Cryptocurrency Markets | [
"q-fin.ST",
"cs.AI"
] | Cryptocurrencies are highly volatile financial instruments with more and more new retail investors joining the scene with each passing day. Bitcoin has always proved to determine in which way the rest of the cryptocurrency market is headed towards. As of today Bitcoin has a market dominance of close to 50 percent. Bull... | {
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2411.13587 | Exploring the Adversarial Vulnerabilities of Vision-Language-Action
Models in Robotics | [
"cs.RO",
"cs.AI"
] | Recently in robotics, Vision-Language-Action (VLA) models have emerged as a transformative approach, enabling robots to execute complex tasks by integrating visual and linguistic inputs within an end-to-end learning framework. While VLA models offer significant capabilities, they also introduce new attack surfaces, mak... | {
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2411.13588 | Unveiling Redundancy in Diffusion Transformers (DiTs): A Systematic
Study | [
"cs.CV",
"cs.AI"
] | The increased model capacity of Diffusion Transformers (DiTs) and the demand for generating higher resolutions of images and videos have led to a significant rise in inference latency, impacting real-time performance adversely. While prior research has highlighted the presence of high similarity in activation values be... | {
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2411.13590 | Deep learning waterways for rural infrastructure development | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Surprisingly a number of Earth's waterways remain unmapped, with a significant number in low and middle income countries. Here we build a computer vision model (WaterNet) to learn the location of waterways in the United States, based on high resolution satellite imagery and digital elevation models, and then deploy thi... | {
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2411.13591 | Improved GUI Grounding via Iterative Narrowing | [
"cs.CV",
"cs.AI",
"cs.CL"
] | Graphical User Interface (GUI) grounding plays a crucial role in enhancing the capabilities of Vision-Language Model (VLM) agents. While general VLMs, such as GPT-4V, demonstrate strong performance across various tasks, their proficiency in GUI grounding remains suboptimal. Recent studies have focused on fine-tuning th... | {
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2411.13592 | A Novel Speech Analysis and Correction Tool for Arabic-Speaking Children | [
"cs.SD",
"cs.AI"
] | This paper introduces a new application named ArPA for Arabic kids who have trouble with pronunciation. Our application comprises two key components: the diagnostic module and the therapeutic module. The diagnostic process involves capturing the child's speech signal, preprocessing, and analyzing it using different mac... | {
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2411.13594 | High resolution microprice estimates from limit orderbook data using
hyperdimensional vector Tsetlin Machines | [
"q-fin.TR",
"cs.LG",
"q-fin.ST"
] | We propose an error-correcting model for the microprice, a high-frequency estimator of future prices given higher order information of imbalances in the orderbook. The model takes into account a current microprice estimate given the spread and best bid to ask imbalance, and adjusts the microprice based on recent dynami... | {
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2411.13595 | Towards Accessible Learning: Deep Learning-Based Potential Dysgraphia
Detection and OCR for Potentially Dysgraphic Handwriting | [
"cs.CV",
"cs.LG"
] | Dysgraphia is a learning disorder that affects handwriting abilities, making it challenging for children to write legibly and consistently. Early detection and monitoring are crucial for providing timely support and interventions. This study applies deep learning techniques to address the dual tasks of dysgraphia detec... | {
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2411.13597 | Enhancing Bidirectional Sign Language Communication: Integrating YOLOv8
and NLP for Real-Time Gesture Recognition & Translation | [
"cs.CV",
"cs.AI"
] | The primary concern of this research is to take American Sign Language (ASL) data through real time camera footage and be able to convert the data and information into text. Adding to that, we are also putting focus on creating a framework that can also convert text into sign language in real time which can help us bre... | {
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2411.13598 | Preserving Expert-Level Privacy in Offline Reinforcement Learning | [
"cs.CR",
"cs.LG"
] | The offline reinforcement learning (RL) problem aims to learn an optimal policy from historical data collected by one or more behavioural policies (experts) by interacting with an environment. However, the individual experts may be privacy-sensitive in that the learnt policy may retain information about their precise c... | {
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2411.13599 | Can ChatGPT Overcome Behavioral Biases in the Financial Sector?
Classify-and-Rethink: Multi-Step Zero-Shot Reasoning in the Gold Investment | [
"q-fin.ST",
"cs.AI"
] | Large Language Models (LLMs) have achieved remarkable success recently, displaying exceptional capabilities in creating understandable and organized text. These LLMs have been utilized in diverse fields, such as clinical research, where domain-specific models like Med-Palm have achieved human-level performance. Recentl... | {
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2411.13602 | Large-scale cross-modality pretrained model enhances cardiovascular
state estimation and cardiomyopathy detection from electrocardiograms: An AI
system development and multi-center validation study | [
"eess.IV",
"cs.AI",
"cs.CV"
] | Cardiovascular diseases (CVDs) present significant challenges for early and accurate diagnosis. While cardiac magnetic resonance imaging (CMR) is the gold standard for assessing cardiac function and diagnosing CVDs, its high cost and technical complexity limit accessibility. In contrast, electrocardiography (ECG) offer... | {
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2411.13603 | A Full-History Network Dataset for BTC Asset Decentralization Profiling | [
"q-fin.ST",
"cs.SI"
] | Since its advent in 2009, Bitcoin (BTC) has garnered increasing attention from both academia and industry. However, due to the massive transaction volume, no systematic study has quantitatively measured the asset decentralization degree specifically from a network perspective. In this paper, by conducting a thorough ... | {
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2411.13604 | RadPhi-3: Small Language Models for Radiology | [
"cs.CV",
"cs.CL",
"cs.LG"
] | LLM based copilot assistants are useful in everyday tasks. There is a proliferation in the exploration of AI assistant use cases to support radiology workflows in a reliable manner. In this work, we present RadPhi-3, a Small Language Model instruction tuned from Phi-3-mini-4k-instruct with 3.8B parameters to assist wit... | {
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2411.13607 | VioPose: Violin Performance 4D Pose Estimation by Hierarchical
Audiovisual Inference | [
"cs.CV"
] | Musicians delicately control their bodies to generate music. Sometimes, their motions are too subtle to be captured by the human eye. To analyze how they move to produce the music, we need to estimate precise 4D human pose (3D pose over time). However, current state-of-the-art (SoTA) visual pose estimation algorithms s... | {
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2411.13608 | Integrating Dynamic Correlation Shifts and Weighted Benchmarking in
Extreme Value Analysis | [
"stat.AP",
"cs.AI"
] | This paper presents an innovative approach to Extreme Value Analysis (EVA) by introducing the Extreme Value Dynamic Benchmarking Method (EVDBM). EVDBM integrates extreme value theory to detect extreme events and is coupled with the novel Dynamic Identification of Significant Correlation (DISC)-Thresholding algorithm, w... | {
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2411.13609 | What You See Is What Matters: A Novel Visual and Physics-Based Metric
for Evaluating Video Generation Quality | [
"cs.CV"
] | As video generation models advance rapidly, assessing the quality of generated videos has become increasingly critical. Existing metrics, such as Fr\'echet Video Distance (FVD), Inception Score (IS), and ClipSim, measure quality primarily in latent space rather than from a human visual perspective, often overlooking ke... | {
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2411.13610 | Video2BEV: Transforming Drone Videos to BEVs for Video-based
Geo-localization | [
"cs.CV"
] | Existing approaches to drone visual geo-localization predominantly adopt the image-based setting, where a single drone-view snapshot is matched with images from other platforms. Such task formulation, however, underutilizes the inherent video output of the drone and is sensitive to occlusions and environmental constrai... | {
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2411.13611 | DSTC: Direct Preference Learning with Only Self-Generated Tests and Code
to Improve Code LMs | [
"cs.SE",
"cs.AI"
] | Direct preference learning offers a promising and computation-efficient beyond supervised fine-tuning (SFT) for improving code generation in coding large language models (LMs). However, the scarcity of reliable preference data is a bottleneck for the performance of direct preference learning to improve the coding accur... | {
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2411.13612 | Efficient Streaming Voice Steganalysis in Challenging Detection
Scenarios | [
"cs.CR",
"cs.LG",
"cs.SD",
"eess.AS"
] | In recent years, there has been an increasing number of information hiding techniques based on network streaming media, focusing on how to covertly and efficiently embed secret information into real-time transmitted network media signals to achieve concealed communication. The misuse of these techniques can lead to sig... | {
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2411.13613 | SuPLE: Robot Learning with Lyapunov Rewards | [
"cs.RO",
"cs.AI"
] | The reward function is an essential component in robot learning. Reward directly affects the sample and computational complexity of learning, and the quality of a solution. The design of informative rewards requires domain knowledge, which is not always available. We use the properties of the dynamics to produce system... | {
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2411.13614 | Verification and Validation of Autonomous Systems | [
"cs.SE",
"cs.AI"
] | This paper describes how to proficiently prevent software defects in autonomous vehicles, discover and correct defects if they are encountered, and create a higher level of assurance in the software product development phase. It also describes how to ensure high assurance on software reliability. | {
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2411.13615 | A Deep Learning Approach to Predict the Fall [of Price] of
Cryptocurrency Long Before its Actual Fall | [
"q-fin.ST",
"cs.CV",
"cs.LG"
] | In modern times, the cryptocurrency market is one of the world's most rapidly rising financial markets. The cryptocurrency market is regarded to be more volatile and illiquid than traditional markets such as equities, foreign exchange, and commodities. The risk of this market creates an uncertain condition among the in... | {
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2411.13619 | Non-Linear Outlier Synthesis for Out-of-Distribution Detection | [
"cs.CV",
"cs.AI",
"cs.LG"
] | The reliability of supervised classifiers is severely hampered by their limitations in dealing with unexpected inputs, leading to great interest in out-of-distribution (OOD) detection. Recently, OOD detectors trained on synthetic outliers, especially those generated by large diffusion models, have shown promising resul... | {
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2411.13620 | Robust SG-NeRF: Robust Scene Graph Aided Neural Surface Reconstruction | [
"cs.CV"
] | Neural surface reconstruction relies heavily on accurate camera poses as input. Despite utilizing advanced pose estimators like COLMAP or ARKit, camera poses can still be noisy. Existing pose-NeRF joint optimization methods handle poses with small noise (inliers) effectively but struggle with large noise (outliers), su... | {
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2411.13623 | Unsupervised Foundation Model-Agnostic Slide-Level Representation
Learning | [
"cs.CV"
] | Representation learning of pathology whole-slide images(WSIs) has primarily relied on weak supervision with Multiple Instance Learning (MIL). This approach leads to slide representations highly tailored to a specific clinical task. Self-supervised learning (SSL) has been successfully applied to train histopathology fou... | {
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2411.13625 | Partition function approach to non-Gaussian likelihoods: information
theory and state variables for Bayesian inference | [
"cond-mat.stat-mech",
"astro-ph.CO",
"cs.IT",
"math.IT"
] | The significance of statistical physics concepts such as entropy extends far beyond classical thermodynamics. We interpret the similarity between partitions in statistical mechanics and partitions in Bayesian inference as an articulation of a result by Jaynes (1957), who clarified that thermodynamics is in essence a th... | {
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2411.13626 | Principles of Visual Tokens for Efficient Video Understanding | [
"cs.CV"
] | Video understanding has made huge strides in recent years, relying largely on the power of the transformer architecture. As this architecture is notoriously expensive and video is highly redundant, research into improving efficiency has become particularly relevant. This has led to many creative solutions, including to... | {
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2411.13627 | CryptoFormalEval: Integrating LLMs and Formal Verification for Automated
Cryptographic Protocol Vulnerability Detection | [
"cs.CR",
"cs.AI",
"cs.SC"
] | Cryptographic protocols play a fundamental role in securing modern digital infrastructure, but they are often deployed without prior formal verification. This could lead to the adoption of distributed systems vulnerable to attack vectors. Formal verification methods, on the other hand, require complex and time-consumin... | {
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2411.13628 | MambaDETR: Query-based Temporal Modeling using State Space Model for
Multi-View 3D Object Detection | [
"cs.CV"
] | Utilizing temporal information to improve the performance of 3D detection has made great progress recently in the field of autonomous driving. Traditional transformer-based temporal fusion methods suffer from quadratic computational cost and information decay as the length of the frame sequence increases. In this paper... | {
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2411.13631 | Sparse Input View Synthesis: 3D Representations and Reliable Priors | [
"cs.CV"
] | Novel view synthesis refers to the problem of synthesizing novel viewpoints of a scene given the images from a few viewpoints. This is a fundamental problem in computer vision and graphics, and enables a vast variety of applications such as meta-verse, free-view watching of events, video gaming, video stabilization and... | {
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2411.13632 | ID-Patch: Robust ID Association for Group Photo Personalization | [
"cs.CV"
] | The ability to synthesize personalized group photos and specify the positions of each identity offers immense creative potential. While such imagery can be visually appealing, it presents significant challenges for existing technologies. A persistent issue is identity (ID) leakage, where injected facial features interf... | {
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2411.13653 | No Free Delivery Service: Epistemic limits of passive data collection in
complex social systems | [
"cs.AI",
"stat.ML"
] | Rapid model validation via the train-test paradigm has been a key driver for the breathtaking progress in machine learning and AI. However, modern AI systems often depend on a combination of tasks and data collection practices that violate all assumptions ensuring test validity. Yet, without rigorous model validation w... | {
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2411.13670 | Graph neural network framework for energy mapping of hybrid monte-carlo
molecular dynamics simulations of Medium Entropy Alloys | [
"cond-mat.mtrl-sci",
"cs.LG"
] | Machine learning (ML) methods have drawn significant interest in material design and discovery. Graph neural networks (GNNs), in particular, have demonstrated strong potential for predicting material properties. The present study proposes a graph-based representation for modeling medium-entropy alloys (MEAs). Hybrid Mo... | {
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2411.13674 | FabuLight-ASD: Unveiling Speech Activity via Body Language | [
"cs.CV",
"cs.LG",
"cs.NE",
"cs.SD",
"eess.AS"
] | Active speaker detection (ASD) in multimodal environments is crucial for various applications, from video conferencing to human-robot interaction. This paper introduces FabuLight-ASD, an advanced ASD model that integrates facial, audio, and body pose information to enhance detection accuracy and robustness. Our model b... | {
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2411.13676 | Hymba: A Hybrid-head Architecture for Small Language Models | [
"cs.CL",
"cs.AI",
"cs.LG"
] | We propose Hymba, a family of small language models featuring a hybrid-head parallel architecture that integrates transformer attention mechanisms with state space models (SSMs) for enhanced efficiency. Attention heads provide high-resolution recall, while SSM heads enable efficient context summarization. Additionally,... | {
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2411.13677 | Bimanual Dexterity for Complex Tasks | [
"cs.RO",
"cs.AI",
"cs.CV",
"cs.LG"
] | To train generalist robot policies, machine learning methods often require a substantial amount of expert human teleoperation data. An ideal robot for humans collecting data is one that closely mimics them: bimanual arms and dexterous hands. However, creating such a bimanual teleoperation system with over 50 DoF is a s... | {
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2411.13681 | Elephant in the Room: Dissecting and Reflecting on the Evolution of
Online Social Network Research | [
"cs.SI"
] | Billions of individuals engage with Online Social Networks (OSN) daily. The owners of OSN try to meet the demands of their end-users while complying with business necessities. Such necessities may, however, lead to the adoption of restrictive data access policies that hinder research activities from "external" scientis... | {
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2411.13682 | Differentially Private Learning Beyond the Classical Dimensionality
Regime | [
"cs.LG",
"cs.CR",
"cs.DS"
] | We initiate the study of differentially private learning in the proportional dimensionality regime, in which the number of data samples $n$ and problem dimension $d$ approach infinity at rates proportional to one another, meaning that $d/n\to\delta$ as $n\to\infty$ for an arbitrary, given constant $\delta\in(0,\infty)$... | {
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} |
2411.13683 | Extending Video Masked Autoencoders to 128 frames | [
"cs.CV"
] | Video understanding has witnessed significant progress with recent video foundation models demonstrating strong performance owing to self-supervised pre-training objectives; Masked Autoencoders (MAE) being the design of choice. Nevertheless, the majority of prior works that leverage MAE pre-training have focused on rel... | {
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2411.13687 | Hierarchical Text Classification (HTC) vs. eXtreme Multilabel
Classification (XML): Two Sides of the Same Medal | [
"cs.CL"
] | Assigning a subset of labels from a fixed pool of labels to a given input text is a text classification problem with many real-world applications, such as in recommender systems. Two separate research streams address this issue. Hierarchical Text Classification (HTC) focuses on datasets with smaller label pools of hund... | {
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2411.13688 | Investigating Graph Neural Networks and Classical Feature-Extraction
Techniques in Activity-Cliff and Molecular Property Prediction | [
"cs.LG",
"q-bio.BM",
"stat.ML"
] | Molecular featurisation refers to the transformation of molecular data into numerical feature vectors. It is one of the key research areas in molecular machine learning and computational drug discovery. Recently, message-passing graph neural networks (GNNs) have emerged as a novel method to learn differentiable feature... | {
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2411.13690 | Multi-Agent Best Arm Identification in Stochastic Linear Bandits | [
"cs.LG"
] | We study the problem of collaborative best-arm identification in stochastic linear bandits under a fixed-budget scenario. In our learning model, we consider multiple agents connected through a star network or a generic network, interacting with a linear bandit instance in parallel. The objective of the agents is to col... | {
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2411.13691 | Retrieval-Augmented Generation for Domain-Specific Question Answering: A
Case Study on Pittsburgh and CMU | [
"cs.LG",
"cs.CL"
] | We designed a Retrieval-Augmented Generation (RAG) system to provide large language models with relevant documents for answering domain-specific questions about Pittsburgh and Carnegie Mellon University (CMU). We extracted over 1,800 subpages using a greedy scraping strategy and employed a hybrid annotation process, co... | {
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2411.13697 | Decompose and Leverage Preferences from Expert Models for Improving
Trustworthiness of MLLMs | [
"cs.CV"
] | Multimodal Large Language Models (MLLMs) can enhance trustworthiness by aligning with human preferences. As human preference labeling is laborious, recent works employ evaluation models for assessing MLLMs' responses, using the model-based assessments to automate preference dataset construction. This approach, however,... | {
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2411.13699 | Test Security in Remote Testing Age: Perspectives from Process Data
Analytics and AI | [
"cs.CR",
"cs.CL",
"cs.HC"
] | The COVID-19 pandemic has accelerated the implementation and acceptance of remotely proctored high-stake assessments. While the flexible administration of the tests brings forth many values, it raises test security-related concerns. Meanwhile, artificial intelligence (AI) has witnessed tremendous advances in the last f... | {
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2411.13700 | A Collaborative Ensemble Framework for CTR Prediction | [
"cs.IR",
"cs.LG"
] | Recent advances in foundation models have established scaling laws that enable the development of larger models to achieve enhanced performance, motivating extensive research into large-scale recommendation models. However, simply increasing the model size in recommendation systems, even with large amounts of data, doe... | {
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2411.13704 | Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse
Ecosystem: Can One QO Rule Them All? | [
"cs.DB"
] | Customer demand, regulatory pressure, and engineering efficiency are the driving forces behind the industry-wide trend of moving from siloed engines and services that are optimized in isolation to highly integrated solutions. This is confirmed by the wide adoption of open formats, shared component libraries, and the me... | {
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} |
2411.13710 | Assessing the Impact of Electric Vehicle Charging on Residential
Distribution Grids | [
"eess.SY",
"cs.SY"
] | To achieve net-zero carbon emissions, electrification in the transportation sector plays an important role. Significant increase of electric vehicles (EV) has been observed nationally and globally. While the transition to EVs presents substantial environmental benefits, it would lead to several challenges to the power ... | {
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} |
2411.13711 | Almost Sure Convergence Rates and Concentration of Stochastic
Approximation and Reinforcement Learning with Markovian Noise | [
"cs.LG",
"math.OC",
"stat.ML"
] | This paper establishes the first almost sure convergence rate and the first maximal concentration bound with exponential tails for general contractive stochastic approximation algorithms with Markovian noise. As a corollary, we also obtain convergence rates in $L^p$. Key to our successes is a novel discretization of th... | {
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} |
2411.13715 | SimPhony: A Device-Circuit-Architecture Cross-Layer Modeling and
Simulation Framework for Heterogeneous Electronic-Photonic AI System | [
"physics.optics",
"cs.AI",
"cs.AR",
"cs.ET",
"cs.LG"
] | Electronic-photonic integrated circuits (EPICs) offer transformative potential for next-generation high-performance AI but require interdisciplinary advances across devices, circuits, architecture, and design automation. The complexity of hybrid systems makes it challenging even for domain experts to understand distinc... | {
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} |
2411.13716 | Developing Normative Gait Cycle Parameters for Clinical Analysis Using
Human Pose Estimation | [
"cs.CV"
] | Gait analysis using computer vision is an emerging field in AI, offering clinicians an objective, multi-feature approach to analyse complex movements. Despite its promise, current applications using RGB video data alone are limited in measuring clinically relevant spatial and temporal kinematics and establishing normat... | {
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} |
2411.13724 | Exploring Large Language Models for Climate Forecasting | [
"cs.LG",
"cs.AI"
] | With the increasing impacts of climate change, there is a growing demand for accessible tools that can provide reliable future climate information to support planning, finance, and other decision-making applications. Large language models (LLMs), such as GPT-4, present a promising approach to bridging the gap between c... | {
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} |
2411.13730 | Replicable Online Learning | [
"cs.LG"
] | We investigate the concept of algorithmic replicability introduced by Impagliazzo et al. 2022, Ghazi et al. 2021, Ahn et al. 2024 in an online setting. In our model, the input sequence received by the online learner is generated from time-varying distributions chosen by an adversary (obliviously). Our objective is to d... | {
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} |
2411.13731 | Delta-Influence: Unlearning Poisons via Influence Functions | [
"cs.CV",
"cs.CR",
"cs.LG"
] | Addressing data integrity challenges, such as unlearning the effects of data poisoning after model training, is necessary for the reliable deployment of machine learning models. State-of-the-art influence functions, such as EK-FAC, often fail to accurately attribute abnormal model behavior to the specific poisoned trai... | {
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} |
2411.13733 | On Generalization Bounds for Neural Networks with Low Rank Layers | [
"cs.LG",
"stat.ML"
] | While previous optimization results have suggested that deep neural networks tend to favour low-rank weight matrices, the implications of this inductive bias on generalization bounds remain underexplored. In this paper, we apply Maurer's chain rule for Gaussian complexity to analyze how low-rank layers in deep networks... | {
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} |
2411.13738 | Assessing Gender Bias in LLMs: Comparing LLM Outputs with Human
Perceptions and Official Statistics | [
"cs.CL",
"cs.LG"
] | This study investigates gender bias in large language models (LLMs) by comparing their gender perception to that of human respondents, U.S. Bureau of Labor Statistics data, and a 50% no-bias benchmark. We created a new evaluation set using occupational data and role-specific sentences. Unlike common benchmarks included... | {
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} |
2411.13740 | Federated Continual Learning for Edge-AI: A Comprehensive Survey | [
"cs.LG",
"cs.AI",
"cs.DC",
"cs.NI"
] | Edge-AI, the convergence of edge computing and artificial intelligence (AI), has become a promising paradigm that enables the deployment of advanced AI models at the network edge, close to users. In Edge-AI, federated continual learning (FCL) has emerged as an imperative framework, which fuses knowledge from different ... | {
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} |
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