id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.03969 | HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for
Industrial Defect Detection | [
"cs.CV"
] | In the manufacturing industry, defect detection is an essential but challenging task aiming to detect defects generated in the process of production. Though traditional YOLO models presents a good performance in defect detection, they still have limitations in capturing high-order feature interrelationships, which hurd... | {
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2412.03970 | A Data-Driven Framework for Discovering Fractional Differential
Equations in Complex Systems | [
"physics.comp-ph",
"cs.AI"
] | In complex physical systems, conventional differential equations often fall short in capturing non-local and memory effects, as they are limited to local dynamics and integer-order interactions. This study introduces a stepwise data-driven framework for discovering fractional differential equations (FDEs) directly from... | {
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2412.03981 | Epoch-based Application of Problem-Aware Operators in a Multiobjective
Memetic Algorithm for Portfolio Optimization | [
"cs.NE"
] | We consider the issue of intensification/diversification balance in the context of a memetic algorithm for the multiobjective optimization of investment portfolios with cardinality constraints. We approach this issue in this work by considering the selective application of knowledge-augmented operators (local search an... | {
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2412.03982 | Exploring Fully Convolutional Networks for the Segmentation of
Hyperspectral Imaging Applied to Advanced Driver Assistance Systems | [
"cs.CV",
"cs.AI",
"cs.LG",
"eess.IV"
] | Advanced Driver Assistance Systems (ADAS) are designed with the main purpose of increasing the safety and comfort of vehicle occupants. Most of current computer vision-based ADAS perform detection and tracking tasks quite successfully under regular conditions, but are not completely reliable, particularly under adverse... | {
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2412.03983 | Safe and Efficient Online Convex Optimization with Linear Budget
Constraints and Partial Feedback | [
"math.OC",
"cs.LG"
] | This paper studies online convex optimization with unknown linear budget constraints, where only the gradient information of the objective and the bandit feedback of constraint functions are observed. We propose a safe and efficient Lyapunov-optimization algorithm (SELO) that can achieve an $O(\sqrt{T})$ regret and zer... | {
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2412.03985 | Design, Characterization, and Validation of a Variable Stiffness
Prosthetic Elbow | [
"cs.RO"
] | Intuitively, prostheses with user-controllable stiffness could mimic the intrinsic behavior of the human musculoskeletal system, promoting safe and natural interactions and task adaptability in real-world scenarios. However, prosthetic design often disregards compliance because of the additional complexity, weight, and... | {
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2412.03986 | UNCOVER: Unknown Class Object Detection for Autonomous Vehicles in
Real-time | [
"cs.CV"
] | Autonomous driving (AD) operates in open-world scenarios, where encountering unknown objects is inevitable. However, standard object detectors trained on a limited number of base classes tend to ignore any unknown objects, posing potential risks on the road. To address this, it is important to learn a generic rather th... | {
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2412.03987 | MTMT: Consolidating Multiple Thinking Modes to Form a Thought Tree for
Strengthening LLM | [
"cs.CL",
"cs.AI"
] | Large language models (LLMs) have shown limitations in tasks requiring complex logical reasoning and multi-step problem-solving. To address these challenges, researchers have employed carefully designed prompts and flowcharts, simulating human cognitive processes to enhance LLM performance, such as the Chain of Thought... | {
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2412.03989 | Semi-automated transmission control for motorcycle gearshift: design,
data-driven tuning and experimental validation | [
"eess.SY",
"cs.SY"
] | This brief addresses the gearshifting problem for Semi-Automated Manual Transmissions (S-AMT) in powered two-wheelers, a powertrain setup that allows fast and smooth gear shifts with minimal modifications to the traditional manual powertrain layout. We show that with a proper synchronization between the electronic clut... | {
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2412.03992 | How well behaved is finite dimensional Diffusion Maps? | [
"stat.ML",
"cs.LG",
"math.ST",
"stat.TH"
] | Under a set of assumptions on a family of submanifolds $\subset {\mathbb R}^D$, we derive a series of geometric properties that remain valid after finite-dimensional and almost isometric Diffusion Maps (DM), including almost uniform density, finite polynomial approximation and local reach. Leveraging these properties, ... | {
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2412.03993 | LaserGuider: A Laser Based Physical Backdoor Attack against Deep Neural
Networks | [
"cs.CR",
"cs.AI",
"cs.CV",
"cs.LG",
"eess.IV"
] | Backdoor attacks embed hidden associations between triggers and targets in deep neural networks (DNNs), causing them to predict the target when a trigger is present while maintaining normal behavior otherwise. Physical backdoor attacks, which use physical objects as triggers, are feasible but lack remote control, tempo... | {
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2412.03995 | Blind Underwater Image Restoration using Co-Operational Regressor
Networks | [
"cs.CV",
"cs.LG",
"eess.IV"
] | The exploration of underwater environments is essential for applications such as biological research, archaeology, and infrastructure maintenanceHowever, underwater imaging is challenging due to the waters unique properties, including scattering, absorption, color distortion, and reduced visibility. To address such vis... | {
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2412.04000 | IF-MDM: Implicit Face Motion Diffusion Model for High-Fidelity Realtime
Talking Head Generation | [
"cs.CV"
] | We introduce a novel approach for high-resolution talking head generation from a single image and audio input. Prior methods using explicit face models, like 3D morphable models (3DMM) and facial landmarks, often fall short in generating high-fidelity videos due to their lack of appearance-aware motion representation. ... | {
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2412.04002 | Hierarchical Learning for IRS-Assisted MEC Systems with Rate-Splitting
Multiple Access | [
"eess.SP",
"cs.IT",
"math.IT"
] | Intelligent reflecting surface (IRS)-assisted mobile edge computing (MEC) systems have shown notable improvements in efficiency, such as reduced latency, higher data rates, and better energy efficiency. However, the resource competition among users will lead to uneven allocation, increased latency, and lower throughput... | {
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2412.04003 | Marco-LLM: Bridging Languages via Massive Multilingual Training for
Cross-Lingual Enhancement | [
"cs.CL"
] | Large Language Models (LLMs) have achieved remarkable progress in recent years; however, their excellent performance is still largely limited to major world languages, primarily English. Many LLMs continue to face challenges with multilingual tasks, especially when it comes to low-resource languages. To address this is... | {
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2412.04006 | Enabling Sustainable Urban Mobility: The Role of 5G Communication in the
Mobilities for EU Project | [
"cs.NI",
"cs.SI",
"eess.SP"
] | This paper examines the role of 5G communication in the Mobilities for EU project, a collaborative initiative involving 29 partners and 11 pilots aimed at revolutionizing urban mobility through electrification, automation, and connectivity. Focusing on Dresden as a Lead City, we explore the integration of 27 innovative... | {
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2412.04008 | Deep-Unrolling Multidimensional Harmonic Retrieval Algorithms on
Neuromorphic Hardware | [
"eess.SP",
"cs.AI",
"cs.AR",
"cs.NE"
] | This paper explores the potential of conversion-based neuromorphic algorithms for highly accurate and energy-efficient single-snapshot multidimensional harmonic retrieval (MHR). By casting the MHR problem as a sparse recovery problem, we devise the currently proposed, deep-unrolling-based Structured Learned Iterative S... | {
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2412.04011 | A Note on Spectral Map | [
"physics.chem-ph",
"cs.LG",
"physics.bio-ph"
] | In molecular dynamics (MD) simulations, transitions between states are often rare events due to energy barriers that exceed the thermal temperature. Because of their infrequent occurrence and the huge number of degrees of freedom in molecular systems, understanding the physical properties that drive rare events is imme... | {
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2412.04020 | PriorMotion: Generative Class-Agnostic Motion Prediction with
Raster-Vector Motion Field Priors | [
"cs.CV",
"cs.PF",
"cs.RO"
] | Reliable perception of spatial and motion information is crucial for safe autonomous navigation. Traditional approaches typically fall into two categories: object-centric and class-agnostic methods. While object-centric methods often struggle with missed detections, leading to inaccuracies in motion prediction, many cl... | {
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2412.04023 | A Model of the Sidewalk Salsa | [
"cs.RO",
"cs.HC"
] | When two pedestrians approach each other on the sidewalk head-on, they sometimes engage in an awkward interaction, both deviating to the same side (repeatedly) to avoid a collision. This phenomenon is known as the sidewalk salsa. Although well known, no existing model describes how this "dance" arises. Such a model mus... | {
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2412.04025 | Exploring the Influence of Label Aggregation on Minority Voices:
Implications for Dataset Bias and Model Training | [
"cs.CL"
] | Resolving disagreement in manual annotation typically consists of removing unreliable annotators and using a label aggregation strategy such as majority vote or expert opinion to resolve disagreement. These may have the side-effect of silencing or under-representing minority but equally valid opinions. In this paper, w... | {
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2412.04026 | M$^{3}$D: A Multimodal, Multilingual and Multitask Dataset for Grounded
Document-level Information Extraction | [
"cs.CL"
] | Multimodal information extraction (IE) tasks have attracted increasing attention because many studies have shown that multimodal information benefits text information extraction. However, existing multimodal IE datasets mainly focus on sentence-level image-facilitated IE in English text, and pay little attention to vid... | {
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2412.04029 | Considerations Influencing Offense-Defense Dynamics From Artificial
Intelligence | [
"cs.AI"
] | The rapid advancement of artificial intelligence (AI) technologies presents profound challenges to societal safety. As AI systems become more capable, accessible, and integrated into critical services, the dual nature of their potential is increasingly clear. While AI can enhance defensive capabilities in areas like th... | {
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2412.04030 | Mask of truth: model sensitivity to unexpected regions of medical images | [
"cs.CV"
] | The development of larger models for medical image analysis has led to increased performance. However, it also affected our ability to explain and validate model decisions. Models can use non-relevant parts of images, also called spurious correlations or shortcuts, to obtain high performance on benchmark datasets but f... | {
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2412.04034 | Dynamic Graph Representation with Contrastive Learning for Financial
Market Prediction: Integrating Temporal Evolution and Static Relations | [
"cs.LG",
"cs.NE",
"q-fin.CP"
] | Temporal Graph Learning (TGL) is crucial for capturing the evolving nature of stock markets. Traditional methods often ignore the interplay between dynamic temporal changes and static relational structures between stocks. To address this issue, we propose the Dynamic Graph Representation with Contrastive Learning (DGRC... | {
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2412.04036 | SocialMind: LLM-based Proactive AR Social Assistive System with
Human-like Perception for In-situ Live Interactions | [
"cs.AI"
] | Social interactions are fundamental to human life. The recent emergence of large language models (LLMs)-based virtual assistants has demonstrated their potential to revolutionize human interactions and lifestyles. However, existing assistive systems mainly provide reactive services to individual users, rather than offe... | {
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2412.04037 | INFP: Audio-Driven Interactive Head Generation in Dyadic Conversations | [
"cs.CV",
"cs.AI"
] | Imagine having a conversation with a socially intelligent agent. It can attentively listen to your words and offer visual and linguistic feedback promptly. This seamless interaction allows for multiple rounds of conversation to flow smoothly and naturally. In pursuit of actualizing it, we propose INFP, a novel audio-dr... | {
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2412.04039 | Benchmarking and Enhancing Surgical Phase Recognition Models for
Robotic-Assisted Esophagectomy | [
"cs.CV"
] | Robotic-assisted minimally invasive esophagectomy (RAMIE) is a recognized treatment for esophageal cancer, offering better patient outcomes compared to open surgery and traditional minimally invasive surgery. RAMIE is highly complex, spanning multiple anatomical areas and involving repetitive phases and non-sequential ... | {
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2412.04041 | GenChaR: A Dataset for Stock Chart Captioning | [
"cs.CE"
] | In this work, we introduce a new dataset GenChaR for an image captioning task around stock charts. The task aims to read market sentiment directly from depicted charts and generate descriptions, hopefully to provide comprehensible and useful insights for stock trading. Impressed by the success of large language models ... | {
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2412.04045 | AI4EF: Artificial Intelligence for Energy Efficiency in the Building
Sector | [
"cs.LG"
] | AI4EF, Artificial Intelligence for Energy Efficiency, is an advanced, user-centric tool designed to support decision-making in building energy retrofitting and efficiency optimization. Leveraging machine learning (ML) and data-driven insights, AI4EF enables stakeholders such as public sector representatives, energy con... | {
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2412.04046 | Hostility Detection in UK Politics: A Dataset on Online Abuse Targeting
MPs | [
"cs.CL"
] | Numerous politicians use social media platforms, particularly X, to engage with their constituents. This interaction allows constituents to pose questions and offer feedback but also exposes politicians to a barrage of hostile responses, especially given the anonymity afforded by social media. They are typically target... | {
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2412.04047 | Pathwise optimization for bridge-type estimators and its applications | [
"stat.ML",
"cs.LG",
"math.ST",
"stat.CO",
"stat.TH"
] | Sparse parametric models are of great interest in statistical learning and are often analyzed by means of regularized estimators. Pathwise methods allow to efficiently compute the full solution path for penalized estimators, for any possible value of the penalization parameter $\lambda$. In this paper we deal with the ... | {
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2412.04050 | A Phase-Field-Micromechanics Study on the Microstructural Evolution
during Viscous Sintering | [
"cs.CE"
] | In the manufacturing process of high-performance particulate materials, viscous sintering plays a crucial role, particularly in fields such as polymer processing and additive manufacturing. The interactions between microscopic particles, their flow behavior, and the evolution of porosity during the viscous sintering pr... | {
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2412.04052 | Learning Dual-Arm Push and Grasp Synergy in Dense Clutter | [
"cs.RO"
] | Robotic grasping in densely cluttered environments is challenging due to scarce collision-free grasp affordances. Non-prehensile actions can increase feasible grasps in cluttered environments, but most research focuses on single-arm rather than dual-arm manipulation. Policies from single-arm systems fail to fully lever... | {
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2412.04054 | Optimal demand response policies for inertial thermal loads under
stochastic renewable sources | [
"eess.SY",
"cs.SY"
] | In this paper, we consider the problem of preferentially utilizing intermittent renewable power, such as wind, optimally to support thermal inertial loads in a microgrid environment. Thermal inertial loads can be programmed to preferentially consume from renewable sources. The flexibility in power consumption of inerti... | {
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2412.04056 | Prompt Engineering Guidance for Conceptual Agent-based Model Extraction
using Large Language Models | [
"cs.MA",
"cs.CY",
"cs.HC"
] | This document contains detailed information about the prompts used in the experimental process discussed in the paper "Toward Automating Agent-based Model Generation: A Benchmark for Model Extraction using Question-Answering Techniques". The paper aims to utilize Question-answering (QA) models to extract the necessary ... | {
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2412.04057 | From Code to Play: Benchmarking Program Search for Games Using Large
Language Models | [
"cs.AI"
] | Large language models (LLMs) have shown impressive capabilities in generating program code, opening exciting opportunities for applying program synthesis to games. In this work, we explore the potential of LLMs to directly synthesize usable code for a wide range of gaming applications, focusing on two programming langu... | {
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2412.04060 | Expand Heterogeneous Learning Systems with Selective Multi-Source
Knowledge Fusion | [
"cs.AI"
] | Expanding existing learning systems to provide high-quality customized models for more domains, such as new users, is challenged by the limited labeled data and the data and device heterogeneities. While knowledge distillation methods could overcome label scarcity and device heterogeneity, they assume the teachers are ... | {
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2412.04062 | ZipAR: Accelerating Auto-regressive Image Generation through Spatial
Locality | [
"cs.CV",
"cs.AI"
] | In this paper, we propose ZipAR, a training-free, plug-and-play parallel decoding framework for accelerating auto-regressive (AR) visual generation. The motivation stems from the observation that images exhibit local structures, and spatially distant regions tend to have minimal interdependence. Given a partially decod... | {
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2412.04064 | Graph Neural Networks Need Cluster-Normalize-Activate Modules | [
"cs.LG",
"cs.AI"
] | Graph Neural Networks (GNNs) are non-Euclidean deep learning models for graph-structured data. Despite their successful and diverse applications, oversmoothing prohibits deep architectures due to node features converging to a single fixed point. This severely limits their potential to solve complex tasks. To counteract... | {
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2412.04065 | Space to Policy: Scalable Brick Kiln Detection and Automatic Compliance
Monitoring with Geospatial Data | [
"cs.LG"
] | Air pollution kills 7 million people annually. The brick kiln sector significantly contributes to economic development but also accounts for 8-14\% of air pollution in India. Policymakers have implemented compliance measures to regulate brick kilns. Emission inventories are critical for air quality modeling and source ... | {
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2412.04067 | Automated Medical Report Generation for ECG Data: Bridging Medical Text
and Signal Processing with Deep Learning | [
"cs.CL",
"cs.AI"
] | Recent advances in deep learning and natural language generation have significantly improved image captioning, enabling automated, human-like descriptions for visual content. In this work, we apply these captioning techniques to generate clinician-like interpretations of ECG data. This study leverages existing ECG data... | {
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2412.04069 | ProtDAT: A Unified Framework for Protein Sequence Design from Any
Protein Text Description | [
"cs.AI"
] | Protein design has become a critical method in advancing significant potential for various applications such as drug development and enzyme engineering. However, protein design methods utilizing large language models with solely pretraining and fine-tuning struggle to capture relationships in multi-modal protein data. ... | {
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2412.04072 | Boundary-Guided Learning for Gene Expression Prediction in Spatial
Transcriptomics | [
"cs.LG"
] | Spatial transcriptomics (ST) has emerged as an advanced technology that provides spatial context to gene expression. Recently, deep learning-based methods have shown the capability to predict gene expression from WSI data using ST data. Existing approaches typically extract features from images and the neighboring regi... | {
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2412.04073 | TransAdapter: Vision Transformer for Feature-Centric Unsupervised Domain
Adaptation | [
"cs.CV"
] | Unsupervised Domain Adaptation (UDA) aims to utilize labeled data from a source domain to solve tasks in an unlabeled target domain, often hindered by significant domain gaps. Traditional CNN-based methods struggle to fully capture complex domain relationships, motivating the shift to vision transformers like the Swin ... | {
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2412.04074 | Integrated Sensing and Communications for Low-Altitude Economy: A Deep
Reinforcement Learning Approach | [
"cs.NI",
"cs.LG"
] | This paper studies an integrated sensing and communications (ISAC) system for low-altitude economy (LAE), where a ground base station (GBS) provides communication and navigation services for authorized unmanned aerial vehicles (UAVs), while sensing the low-altitude airspace to monitor the unauthorized mobile target. Th... | {
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2412.04075 | Does your model understand genes? A benchmark of gene properties for
biological and text models | [
"cs.AI"
] | The application of deep learning methods, particularly foundation models, in biological research has surged in recent years. These models can be text-based or trained on underlying biological data, especially omics data of various types. However, comparing the performance of these models consistently has proven to be a... | {
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2412.04076 | Distance-Adaptive Quaternion Knowledge Graph Embedding with
Bidirectional Rotation | [
"cs.LG"
] | Quaternion contains one real part and three imaginary parts, which provided a more expressive hypercomplex space for learning knowledge graph. Existing quaternion embedding models measure the plausibility of a triplet either through semantic matching or geometric distance scoring functions. However, it appears that sem... | {
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2412.04077 | SoRA: Singular Value Decomposed Low-Rank Adaptation for Domain
Generalizable Representation Learning | [
"cs.CV"
] | Domain generalization (DG) aims to adapt a model using one or multiple source domains to ensure robust performance in unseen target domains. Recently, Parameter-Efficient Fine-Tuning (PEFT) of foundation models has shown promising results in the context of DG problem. Nevertheless, existing PEFT methods still struggle ... | {
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2412.04078 | Mind the Gap: Towards Generalizable Autonomous Penetration Testing via
Domain Randomization and Meta-Reinforcement Learning | [
"cs.LG",
"cs.CR"
] | With increasing numbers of vulnerabilities exposed on the internet, autonomous penetration testing (pentesting) has emerged as a promising research area. Reinforcement learning (RL) is a natural fit for studying this topic. However, two key challenges limit the applicability of RL-based autonomous pentesting in real-wo... | {
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2412.04081 | Federated Learning in Mobile Networks: A Comprehensive Case Study on
Traffic Forecasting | [
"cs.LG",
"cs.AI"
] | The increasing demand for efficient resource allocation in mobile networks has catalyzed the exploration of innovative solutions that could enhance the task of real-time cellular traffic prediction. Under these circumstances, federated learning (FL) stands out as a distributed and privacy-preserving solution to foster ... | {
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2412.04082 | Learnable Similarity and Dissimilarity Guided Symmetric Non-Negative
Matrix Factorization | [
"cs.LG"
] | Symmetric nonnegative matrix factorization (SymNMF) is a powerful tool for clustering, which typically uses the $k$-nearest neighbor ($k$-NN) method to construct similarity matrix. However, $k$-NN may mislead clustering since the neighbors may belong to different clusters, and its reliability generally decreases as $k$... | {
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2412.04083 | Unified Framework for Open-World Compositional Zero-shot Learning | [
"cs.CV"
] | Open-World Compositional Zero-Shot Learning (OW-CZSL) addresses the challenge of recognizing novel compositions of known primitives and entities. Even though prior works utilize language knowledge for recognition, such approaches exhibit limited interactions between language-image modalities. Our approach primarily foc... | {
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2412.04086 | BodyMetric: Evaluating the Realism of Human Bodies in Text-to-Image
Generation | [
"cs.CV",
"cs.AI"
] | Accurately generating images of human bodies from text remains a challenging problem for state of the art text-to-image models. Commonly observed body-related artifacts include extra or missing limbs, unrealistic poses, blurred body parts, etc. Currently, evaluation of such artifacts relies heavily on time-consuming hu... | {
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2412.04090 | LossAgent: Towards Any Optimization Objectives for Image Processing with
LLM Agents | [
"cs.CV"
] | We present the first loss agent, dubbed LossAgent, for low-level image processing tasks, e.g., image super-resolution and restoration, intending to achieve any customized optimization objectives of low-level image processing in different practical applications. Notably, not all optimization objectives, such as complex ... | {
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2412.04092 | GEITje 7B Ultra: A Conversational Model for Dutch | [
"cs.CL"
] | Language models have rapidly evolved, predominantly focusing on English while often neglecting extensive pretraining in other languages. This approach has required initiatives to adapt powerful, English-centric models to other linguistic contexts through finetuning. For Dutch, such a recent endeavour is ``GEITje'' a mo... | {
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2412.04093 | Practical Considerations for Agentic LLM Systems | [
"cs.AI"
] | As the strength of Large Language Models (LLMs) has grown over recent years, so too has interest in their use as the underlying models for autonomous agents. Although LLMs demonstrate emergent abilities and broad expertise across natural language domains, their inherent unpredictability makes the implementation of LLM ... | {
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2412.04094 | Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble
for Enhanced Brain Tumor Segmentation | [
"eess.IV",
"cs.CV"
] | Accurate and automatic segmentation of brain tumors in multi-parametric magnetic resonance imaging (mpMRI) is essential for quantitative measurements, which play an increasingly important role in clinical diagnosis and prognosis. The International Brain Tumor Segmentation (BraTS) Challenge 2024 offers a unique benchmar... | {
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2412.04095 | HyperFLINT: Hypernetwork-based Flow Estimation and Temporal
Interpolation for Scientific Ensemble Visualization | [
"cs.CV",
"cs.GR",
"cs.LG"
] | We present HyperFLINT (Hypernetwork-based FLow estimation and temporal INTerpolation), a novel deep learning-based approach for estimating flow fields, temporally interpolating scalar fields, and facilitating parameter space exploration in spatio-temporal scientific ensemble data. This work addresses the critical need ... | {
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2412.04097 | D-LORD for Motion Stylization | [
"cs.CV",
"cs.AI"
] | This paper introduces a novel framework named D-LORD (Double Latent Optimization for Representation Disentanglement), which is designed for motion stylization (motion style transfer and motion retargeting). The primary objective of this framework is to separate the class and content information from a given motion sequ... | {
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2412.04100 | Missing Melodies: AI Music Generation and its "Nearly" Complete Omission
of the Global South | [
"cs.SD",
"cs.AI",
"cs.CL",
"cs.LG",
"eess.AS"
] | Recent advances in generative AI have sparked renewed interest and expanded possibilities for music generation. However, the performance and versatility of these systems across musical genres are heavily influenced by the availability of training data. We conducted an extensive analysis of over one million hours of aud... | {
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2412.04101 | Database Theory + X: Database Visualization | [
"cs.DB",
"cs.HC"
] | We draw a connection between data modeling and visualization, namely that a visualization specification defines a mapping from database constraints to visual representations of those constraints. Using this formalism, we show how many visualization design decisions are, in fact, data modeling choices and extend data vi... | {
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2412.04106 | MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation
towards Unannotated Modalities | [
"cs.CV",
"cs.AI"
] | Medical image segmentation has recently demonstrated impressive progress with deep neural networks, yet the heterogeneous modalities and scarcity of mask annotations limit the development of segmentation models on unannotated modalities. This paper investigates a new paradigm for leveraging generative models in medical... | {
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2412.04107 | Pre-train, Align, and Disentangle: Empowering Sequential Recommendation
with Large Language Models | [
"cs.IR",
"cs.AI"
] | Sequential recommendation (SR) aims to model the sequential dependencies in users' historical interactions to better capture their evolving interests. However, existing SR approaches primarily rely on collaborative data, which leads to limitations such as the cold-start problem and sub-optimal performance. Meanwhile, d... | {
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2412.04110 | Enhancing Mathematical Reasoning in LLMs with Background Operators | [
"cs.AI"
] | We propose utilizing background operators for mathematical reasoning in large language models (LLMs). To achieve this, we define a set of fundamental mathematical predicates as the basic building blocks. For each mathematical problem, we develop a Prolog solution that includes problem-specific predicates and intermedia... | {
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2412.04111 | Adult Glioma Segmentation in Sub-Saharan Africa using Transfer Learning
on Stratified Finetuning Data | [
"eess.IV",
"cs.CV"
] | Gliomas, a kind of brain tumor characterized by high mortality, present substantial diagnostic challenges in low- and middle-income countries, particularly in Sub-Saharan Africa. This paper introduces a novel approach to glioma segmentation using transfer learning to address challenges in resource-limited regions with ... | {
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2412.04114 | Thermal and RGB Images Work Better Together in Wind Turbine Damage
Detection | [
"cs.CV",
"cs.AI",
"cs.RO"
] | The inspection of wind turbine blades (WTBs) is crucial for ensuring their structural integrity and operational efficiency. Traditional inspection methods can be dangerous and inefficient, prompting the use of unmanned aerial vehicles (UAVs) that access hard-to-reach areas and capture high-resolution imagery. In this s... | {
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2412.04117 | MVUDA: Unsupervised Domain Adaptation for Multi-view Pedestrian
Detection | [
"cs.CV"
] | We address multi-view pedestrian detection in a setting where labeled data is collected using a multi-camera setup different from the one used for testing. While recent multi-view pedestrian detectors perform well on the camera rig used for training, their performance declines when applied to a different setup. To faci... | {
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2412.04119 | GRAF: Graph Retrieval Augmented by Facts for Romanian Legal Multi-Choice
Question Answering | [
"cs.CL"
] | Pre-trained Language Models (PLMs) have shown remarkable performances in recent years, setting a new paradigm for NLP research and industry. The legal domain has received some attention from the NLP community partly due to its textual nature. Some tasks from this domain are represented by question-answering (QA) tasks.... | {
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2412.04120 | CrossSDF: 3D Reconstruction of Thin Structures From Cross-Sections | [
"cs.CV"
] | Reconstructing complex structures from planar cross-sections is a challenging problem, with wide-reaching applications in medical imaging, manufacturing, and topography. Out-of-the-box point cloud reconstruction methods can often fail due to the data sparsity between slicing planes, while current bespoke methods strugg... | {
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2412.04121 | DeepFEA: Deep Learning for Prediction of Transient Finite Element
Analysis Solutions | [
"cs.LG",
"cs.AI",
"cs.CE"
] | Finite Element Analysis (FEA) is a powerful but computationally intensive method for simulating physical phenomena. Recent advancements in machine learning have led to surrogate models capable of accelerating FEA. Yet there are still limitations in developing surrogates of transient FEA models that can simultaneously p... | {
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2412.04129 | Towards Fast and Safety-Guaranteed Trajectory Planning and Tracking for
Time-Varying Systems | [
"eess.SY",
"cs.RO",
"cs.SY",
"math.OC"
] | When deploying autonomous systems in unknown and changing environments, it is critical that their motion planning and control algorithms are computationally efficient and can be reapplied online in real time, whilst providing theoretical safety guarantees in the presence of disturbances. The satisfaction of these objec... | {
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2412.04130 | Deep priors for satellite image restoration with accurate uncertainties | [
"cs.CV",
"eess.IV",
"physics.optics"
] | Satellite optical images, upon their on-ground receipt, offer a distorted view of the observed scene. Their restoration, classically including denoising, deblurring, and sometimes super-resolution, is required before their exploitation. Moreover, quantifying the uncertainty related to this restoration could be valuable... | {
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2412.04131 | Decentralized Dynamic Event-triggered Output-feedback Control of
Stochastic Non-triangular Interconnected Systems with Unknown Time-varying
Sensor Sensitivity | [
"eess.SY",
"cs.SY"
] | This study addresses the intricate challenge of decentralized output-feedback control for stochastic non-triangular nonlinear interconnected systems with unknown time-varying sensor sensitivity in a dynamic event-triggered context. The presence of stochastic disturbances, non-triangular structural uncertainties, and ev... | {
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2412.04132 | Towards Comprehensive Legislative Requirements for Cyber Physical
Systems Testing in the European Union | [
"cs.SE",
"cs.CY",
"cs.SY",
"eess.SY"
] | While procedures prevail on the European market for the greater good of its citizens, it might be daunting when trying to introduce a product, whether innovative or not. In the current world, Cyber-Physical Systems (CPSs) are ubiquitous in our daily lives. Cars can provide intrusive assistance as they can brake or turn... | {
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2412.04134 | Compositional Generative Multiphysics and Multi-component Simulation | [
"cs.LG"
] | Multiphysics simulation, which models the interactions between multiple physical processes, and multi-component simulation of complex structures are critical in fields like nuclear and aerospace engineering. Previous studies often rely on numerical solvers or machine learning-based surrogate models to solve or accelera... | {
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2412.04137 | Text Change Detection in Multilingual Documents Using Image Comparison | [
"cs.CV",
"cs.AI",
"cs.CL",
"cs.LG"
] | Document comparison typically relies on optical character recognition (OCR) as its core technology. However, OCR requires the selection of appropriate language models for each document and the performance of multilingual or hybrid models remains limited. To overcome these challenges, we propose text change detection (T... | {
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2412.04139 | Monet: Mixture of Monosemantic Experts for Transformers | [
"cs.AI"
] | Understanding the internal computations of large language models (LLMs) is crucial for aligning them with human values and preventing undesirable behaviors like toxic content generation. However, mechanistic interpretability is hindered by polysemanticity -- where individual neurons respond to multiple, unrelated conce... | {
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2412.04140 | Understanding Memorization in Generative Models via Sharpness in
Probability Landscapes | [
"cs.LG",
"cs.AI"
] | In this paper, we introduce a geometric framework to analyze memorization in diffusion models using the eigenvalues of the Hessian of the log probability density. We propose that memorization arises from isolated points in the learned probability distribution, characterized by sharpness in the probability landscape, as... | {
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2412.04141 | Reducing Tool Hallucination via Reliability Alignment | [
"cs.CL"
] | Large Language Models (LLMs) have extended their capabilities beyond language generation to interact with external systems through tool calling, offering powerful potential for real-world applications. However, the phenomenon of tool hallucinations, which occur when models improperly select or misuse tools, presents cr... | {
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2412.04142 | Methodology for Online Estimation of Rheological Parameters in Polymer
Melts Using Deep Learning and Microfluidics | [
"physics.flu-dyn",
"cs.AI"
] | Microfluidic devices are increasingly used in biological and chemical experiments due to their cost-effectiveness for rheological estimation in fluids. However, these devices often face challenges in terms of accuracy, size, and cost. This study presents a methodology, integrating deep learning, modeling and simulation... | {
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2412.04144 | If You Can't Use Them, Recycle Them: Optimizing Merging at Scale
Mitigates Performance Tradeoffs | [
"cs.CL",
"cs.AI"
] | Model merging has shown great promise at combining expert models, but the benefit of merging is unclear when merging "generalist" models trained on many tasks. We explore merging in the context of large (~100B) models, by recycling checkpoints that exhibit tradeoffs among different tasks. Such checkpoints are often cre... | {
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2412.04146 | AnyDressing: Customizable Multi-Garment Virtual Dressing via Latent
Diffusion Models | [
"cs.CV"
] | Recent advances in garment-centric image generation from text and image prompts based on diffusion models are impressive. However, existing methods lack support for various combinations of attire, and struggle to preserve the garment details while maintaining faithfulness to the text prompts, limiting their performance... | {
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2412.04147 | MultiTASC++: A Continuously Adaptive Scheduler for Edge-Based
Multi-Device Cascade Inference | [
"cs.LG",
"cs.DC"
] | Cascade systems, consisting of a lightweight model processing all samples and a heavier, high-accuracy model refining challenging samples, have become a widely-adopted distributed inference approach to achieving high accuracy and maintaining a low computational burden for mobile and IoT devices. As intelligent indoor e... | {
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2412.04148 | Recursively Extended Permutation Codes under Chebyshev Distance | [
"cs.IT",
"math.IT"
] | This paper investigates the construction and analysis of permutation codes under the Chebyshev distance. The direct product group permutation (DPGP) codes, introduced independently by Kl\o ve et al. and Tamo et al., represent the best-known permutation codes in terms of both size and minimum distance. These codes posse... | {
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2412.04149 | Frequency-Adaptive Low-Latency Object Detection Using Events and Frames | [
"cs.CV",
"cs.AI"
] | Fusing Events and RGB images for object detection leverages the robustness of Event cameras in adverse environments and the rich semantic information provided by RGB cameras. However, two critical mismatches: low-latency Events \textit{vs.}~high-latency RGB frames; temporally sparse labels in training \textit{vs.}~cont... | {
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2412.04153 | A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of
Navigation Tasks | [
"cs.RO",
"math.OC"
] | Reinforcement learning (RL) has been successfully applied to a variety of robotics applications, where it outperforms classical methods. However, the safety aspect of RL and the transfer to the real world remain an open challenge. A prominent field for tackling this challenge and ensuring the safety of the agents durin... | {
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2412.04157 | Non-Asymptotic Bounds for Closed-Loop Identification of Unstable
Nonlinear Stochastic Systems | [
"eess.SY",
"cs.LG",
"cs.SY",
"math.OC"
] | We consider the problem of least squares parameter estimation from single-trajectory data for discrete-time, unstable, closed-loop nonlinear stochastic systems, with linearly parameterised uncertainty. Assuming a region of the state space produces informative data, and the system is sub-exponentially unstable, we estab... | {
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2412.04158 | LossVal: Efficient Data Valuation for Neural Networks | [
"cs.LG"
] | Assessing the importance of individual training samples is a key challenge in machine learning. Traditional approaches retrain models with and without specific samples, which is computationally expensive and ignores dependencies between data points. We introduce LossVal, an efficient data valuation method that computes... | {
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2412.04163 | On the Lack of Robustness of Binary Function Similarity Systems | [
"cs.CR",
"cs.LG"
] | Binary function similarity, which often relies on learning-based algorithms to identify what functions in a pool are most similar to a given query function, is a sought-after topic in different communities, including machine learning, software engineering, and security. Its importance stems from the impact it has in fa... | {
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2412.04166 | An In-Depth Examination of Risk Assessment in Multi-Class Classification
Algorithms | [
"cs.LG",
"cs.NA",
"math.NA"
] | Advanced classification algorithms are being increasingly used in safety-critical applications like health-care, engineering, etc. In such applications, miss-classifications made by ML algorithms can result in substantial financial or health-related losses. To better anticipate and prepare for such losses, the algorith... | {
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2412.04167 | Bench-CoE: a Framework for Collaboration of Experts from Benchmark | [
"cs.AI"
] | Large Language Models (LLMs) are key technologies driving intelligent systems to handle multiple tasks. To meet the demands of various tasks, an increasing number of LLMs-driven experts with diverse capabilities have been developed, accompanied by corresponding benchmarks to evaluate their performance. This paper propo... | {
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} |
2412.04174 | Supertoroid fitting of objects with holes for robotic grasping and scene
generation | [
"eess.IV",
"cs.RO"
] | One of the strategies to detect the pose and shape of unknown objects is their geometric modeling, consisting on fitting known geometric entities. Classical geometric modeling fits simple shapes such as spheres or cylinders, but often those don't cover the variety of shapes that can be encountered. For those situations... | {
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} |
2412.04177 | Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning | [
"cs.LG",
"stat.ML"
] | Recently, there has been an increasing interest in performing post-hoc uncertainty estimation about the predictions of pre-trained deep neural networks (DNNs). Given a pre-trained DNN via back-propagation, these methods enhance the original network by adding output confidence measures, such as error bars, without compr... | {
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} |
2412.04178 | Multi-Layer Privacy-Preserving Record Linkage with Clerical Review based
on gradual information disclosure | [
"cs.CR",
"cs.DB",
"cs.LG"
] | Privacy-Preserving Record linkage (PPRL) is an essential component in data integration tasks of sensitive information. The linkage quality determines the usability of combined datasets and (machine learning) applications based on them. We present a novel privacy-preserving protocol that integrates clerical review in PP... | {
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} |
2412.04180 | SKIM: Any-bit Quantization Pushing The Limits of Post-Training
Quantization | [
"cs.LG"
] | Large Language Models (LLMs) exhibit impressive performance across various tasks, but deploying them for inference poses challenges. Their high resource demands often necessitate complex, costly multi-GPU pipelines, or the use of smaller, less capable models. While quantization offers a promising solution utilizing low... | {
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} |
2412.04183 | Linear Discriminant Analysis in Credit Scoring: A Transparent Hybrid
Model Approach | [
"cs.LG"
] | The development of computing has made credit scoring approaches possible, with various machine learning (ML) and deep learning (DL) techniques becoming more and more valuable. While complex models yield more accurate predictions, their interpretability is often weakened, which is a concern for credit scoring that place... | {
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} |
2412.04184 | Modeling Eye Gaze Velocity Trajectories using GANs with Spectral Loss
for Enhanced Fidelity | [
"cs.NE",
"cs.LG"
] | Accurate modeling of eye gaze dynamics is essential for advancement in human-computer interaction, neurological diagnostics, and cognitive research. Traditional generative models like Markov models often fail to capture the complex temporal dependencies and distributional nuance inherent in eye gaze trajectories data. ... | {
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} |
2412.04185 | Leveraging Large Language Models to Generate Course-specific
Semantically Annotated Learning Objects | [
"cs.AI"
] | Background: Over the past few decades, the process and methodology of automated question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potentia... | {
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} |
2412.04188 | Utilizing phase-type distributions for queueing-based railway junction
performance determination | [
"eess.SY",
"cs.SY"
] | To ensure the effective and objective development of transportation networks, it is crucial to identify performance limitations across various subsystems. A timetable-independent assessment of infrastructure capacity at railway junctions is a fundamental aspect of long-term rail network planning. While recent research ... | {
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} |
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