id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2411.08195 | An Explainable Machine Learning Approach for Age and Gender Estimation
in Living Individuals Using Dental Biometrics | [
"cs.CV",
"cs.AI"
] | Objectives: Age and gender estimation is crucial for various applications, including forensic investigations and anthropological studies. This research aims to develop a predictive system for age and gender estimation in living individuals, leveraging dental measurements such as Coronal Height (CH), Coronal Pulp Cavity... | {
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2411.08196 | Latent Space Disentanglement in Diffusion Transformers Enables Precise
Zero-shot Semantic Editing | [
"cs.CV"
] | Diffusion Transformers (DiTs) have recently achieved remarkable success in text-guided image generation. In image editing, DiTs project text and image inputs to a joint latent space, from which they decode and synthesize new images. However, it remains largely unexplored how multimodal information collectively forms th... | {
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2411.08197 | What Representational Similarity Measures Imply about Decodable
Information | [
"stat.ML",
"cs.AI",
"cs.LG"
] | Neural responses encode information that is useful for a variety of downstream tasks. A common approach to understand these systems is to build regression models or ``decoders'' that reconstruct features of the stimulus from neural responses. Popular neural network similarity measures like centered kernel alignment (CK... | {
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2411.08199 | System-Level Analysis for mm-Wave Full-Duplex Transceivers | [
"eess.SY",
"cs.SY"
] | This paper conducts a comprehensive system-level analysis of mm-Wave full-duplex transceivers, focusing on a receiver employing a four-stage self-interference cancellation (SIC) process. The analysis aims to optimize the noise and linearity performance requirements of each transceiver block, ensuring that the self-inte... | {
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2411.08203 | FaaS and Furious: abstractions and differential caching for efficient
data pre-processing | [
"cs.DB"
] | Data pre-processing pipelines are the bread and butter of any successful AI project. We introduce a novel programming model for pipelines in a data lakehouse, allowing users to interact declaratively with assets in object storage. Motivated by real-world industry usage patterns, we exploit these new abstractions with a... | {
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2411.08206 | Lua API and benchmark design using 3n+1 sequences: Comparing API
elegance and raw speed in Redis and YottaDB databases | [
"cs.DB",
"cs.PL"
] | Elegance of a database API matters to the programmer. Frequently, database APIs provide rudimentary functionality without thinking about the programmer's desire for elegant yet efficient syntax. This article discusses API design that is both elegant and efficient. It does so, firstly, by comparing the Lua APIs for two ... | {
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2411.08212 | PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert
Model | [
"cs.LG",
"cs.AI"
] | The Mixture-of-Experts (MoE) paradigm has emerged as a powerful approach for scaling transformers with improved resource utilization. However, efficiently fine-tuning MoE models remains largely underexplored. Inspired by recent works on Parameter-Efficient Fine-Tuning (PEFT), we present a unified framework for integrat... | {
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2411.08216 | GTA: Global Tracklet Association for Multi-Object Tracking in Sports | [
"cs.CV"
] | Multi-object tracking in sports scenarios has become one of the focal points in computer vision, experiencing significant advancements through the integration of deep learning techniques. Despite these breakthroughs, challenges remain, such as accurately re-identifying players upon re-entry into the scene and minimizin... | {
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2411.08221 | SynapsNet: Enhancing Neuronal Population Dynamics Modeling via Learning
Functional Connectivity | [
"q-bio.NC",
"cs.LG"
] | The availability of large-scale neuronal population datasets necessitates new methods to model population dynamics and extract interpretable, scientifically translatable insights. Existing deep learning methods often overlook the biological mechanisms underlying population activity and thus exhibit suboptimal performan... | {
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2411.08224 | Joint Diffusion models in Continual Learning | [
"cs.LG"
] | In this work, we introduce JDCL - a new method for continual learning with generative rehearsal based on joint diffusion models. Neural networks suffer from catastrophic forgetting defined as abrupt loss in the model's performance when retrained with additional data coming from a different distribution. Generative-repl... | {
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2411.08227 | DPU: Dynamic Prototype Updating for Multimodal Out-of-Distribution
Detection | [
"cs.CV",
"cs.AI"
] | Out-of-distribution (OOD) detection is essential for ensuring the robustness of machine learning models by identifying samples that deviate from the training distribution. While traditional OOD detection has primarily focused on single-modality inputs, such as images, recent advances in multimodal models have demonstra... | {
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2411.08231 | Enhanced Monocular Visual Odometry with AR Poses and Integrated INS-GPS
for Robust Localization in Urban Environments | [
"cs.RO"
] | This paper introduces a cost effective localization system combining monocular visual odometry , augmented reality (AR) poses, and integrated INS-GPS data. We address monocular VO scale factor issues using AR poses and enhance accuracy with INS and GPS data, filtered through an Extended Kalman Filter . Our approach, te... | {
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2411.08232 | Imitation Learning from Observations: An Autoregressive Mixture of
Experts Approach | [
"cs.LG",
"math.OC"
] | This paper presents a novel approach to imitation learning from observations, where an autoregressive mixture of experts model is deployed to fit the underlying policy. The parameters of the model are learned via a two-stage framework. By leveraging the existing dynamics knowledge, the first stage of the framework esti... | {
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2411.08233 | Improved Constructions of Skew-Tolerant Gray Codes | [
"cs.IT",
"cs.DM",
"math.CO",
"math.IT"
] | We study skew-tolerant Gray codes, which are Gray codes in which changes in consecutive codewords occur in adjacent positions. We present the first construction of asymptotically non-vanishing skew-tolerant Gray codes, offering an exponential improvement over the known construction. We also provide linear-time encoding... | {
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2411.08241 | A Social Outcomes and Priorities centered (SOP) Framework for AI policy | [
"cs.CY",
"cs.AI",
"cs.LG"
] | Rapid developments in AI and its adoption across various domains have necessitated a need to build robust guardrails and risk containment plans while ensuring equitable benefits for the betterment of society. The current technology-centered approach has resulted in a fragmented, reactive, and ineffective policy apparat... | {
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2411.08243 | Beyond the Safety Bundle: Auditing the Helpful and Harmless Dataset | [
"cs.CL",
"cs.CY"
] | In an effort to mitigate the harms of large language models (LLMs), learning from human feedback (LHF) has been used to steer LLMs towards outputs that are intended to be both less harmful and more helpful. Despite the widespread adoption of LHF in practice, the quality of this feedback and its effectiveness as a safet... | {
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2411.08244 | NVCiM-PT: An NVCiM-assisted Prompt Tuning Framework for Edge LLMs | [
"cs.LG",
"cs.ET"
] | Large Language Models (LLMs) deployed on edge devices, known as edge LLMs, need to continuously fine-tune their model parameters from user-generated data under limited resource constraints. However, most existing learning methods are not applicable for edge LLMs because of their reliance on high resources and low learn... | {
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2411.08248 | Deceiving Question-Answering Models: A Hybrid Word-Level Adversarial
Approach | [
"cs.CL",
"cs.AI",
"cs.LG"
] | Deep learning underpins most of the currently advanced natural language processing (NLP) tasks such as textual classification, neural machine translation (NMT), abstractive summarization and question-answering (QA). However, the robustness of the models, particularly QA models, against adversarial attacks is a critical... | {
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2411.08249 | Retrieval Augmented Time Series Forecasting | [
"cs.LG",
"cs.AI"
] | Retrieval-augmented generation (RAG) is a central component of modern LLM systems, particularly in scenarios where up-to-date information is crucial for accurately responding to user queries or when queries exceed the scope of the training data. The advent of time-series foundation models (TSFM), such as Chronos, and t... | {
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2411.08250 | What Are The Risks of Living in a GenAI Synthetic Reality? The
Generative AI Paradox | [
"cs.SI"
] | Generative AI (GenAI) technologies possess unprecedented potential to reshape our world and our perception of reality. These technologies can amplify traditionally human-centered capabilities, such as creativity and complex problem-solving in socio-technical contexts. By fostering human-AI collaboration, GenAI could en... | {
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2411.08253 | Open-World Task and Motion Planning via Vision-Language Model Inferred
Constraints | [
"cs.RO"
] | Foundation models trained on internet-scale data, such as Vision-Language Models (VLMs), excel at performing tasks involving common sense, such as visual question answering. Despite their impressive capabilities, these models cannot currently be directly applied to challenging robot manipulation problems that require c... | {
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2411.08254 | VALTEST: Automated Validation of Language Model Generated Test Cases | [
"cs.SE",
"cs.AI"
] | Large Language Models (LLMs) have demonstrated significant potential in automating software testing, specifically in generating unit test cases. However, the validation of LLM-generated test cases remains a challenge, particularly when the ground truth is unavailable. This paper introduces VALTEST, a novel framework de... | {
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2411.08257 | GPTree: Towards Explainable Decision-Making via LLM-powered Decision
Trees | [
"cs.LG",
"cs.AI",
"cs.CE"
] | Traditional decision tree algorithms are explainable but struggle with non-linear, high-dimensional data, limiting its applicability in complex decision-making. Neural networks excel at capturing complex patterns but sacrifice explainability in the process. In this work, we present GPTree, a novel framework combining e... | {
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2411.08258 | Efficient encoding and decoding algorithm for a class of perfect
single-deletion-correcting permutation codes | [
"cs.IT",
"math.CO",
"math.IT"
] | A permutation code is a nonlinear code whose codewords are permutation of a set of symbols. We consider the use of permutation code in the deletion channel, and consider the symbol-invariant error model, meaning that the values of the symbols that are not removed are not affected by the deletion. In 1992, Levenshtein g... | {
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2411.08261 | Control of Biohybrid Actuators using NeuroEvolution | [
"cs.RO",
"cs.ET"
] | In medical-related tasks, soft robots can perform better than conventional robots because of their compliant building materials and the movements they are able perform. However, designing soft robot controllers is not an easy task, due to the non-linear properties of their materials. Since human expertise to design suc... | {
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2411.08267 | Least Squares Training of Quadratic Convolutional Neural Networks with
Applications to System Theory | [
"cs.LG"
] | This paper provides a least squares formulation for the training of a 2-layer convolutional neural network using quadratic activation functions, a 2-norm loss function, and no regularization term. Using this method, an analytic expression for the globally optimal weights is obtained alongside a quadratic input-output e... | {
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2411.08272 | LBONet: Supervised Spectral Descriptors for Shape Analysis | [
"cs.CV"
] | The Laplace-Beltrami operator has established itself in the field of non-rigid shape analysis due to its many useful properties such as being invariant under isometric transformation, having a countable eigensystem forming an orthonormal basis, and fully characterizing geodesic distances of the manifold. However, this ... | {
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2411.08275 | A Large-Scale Study of Relevance Assessments with Large Language Models:
An Initial Look | [
"cs.IR",
"cs.CL"
] | The application of large language models to provide relevance assessments presents exciting opportunities to advance information retrieval, natural language processing, and beyond, but to date many unknowns remain. This paper reports on the results of a large-scale evaluation (the TREC 2024 RAG Track) where four differ... | {
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2411.08278 | Knowledge Bases in Support of Large Language Models for Processing Web
News | [
"cs.CL",
"cs.AI"
] | Large Language Models (LLMs) have received considerable interest in wide applications lately. During pre-training via massive datasets, such a model implicitly memorizes the factual knowledge of trained datasets in its hidden parameters. However, knowledge held implicitly in parameters often makes its use by downstream... | {
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2411.08279 | MBA-SLAM: Motion Blur Aware Dense Visual SLAM with Radiance Fields
Representation | [
"cs.CV",
"cs.RO"
] | Emerging 3D scene representations, such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have demonstrated their effectiveness in Simultaneous Localization and Mapping (SLAM) for photo-realistic rendering, particularly when using high-quality video sequences as input. However, existing methods struggl... | {
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2411.08281 | When to Localize? A POMDP Approach | [
"cs.RO"
] | Robots often localize to lower navigational errors and facilitate downstream, high-level tasks. However, a robot may want to selectively localize when localization is costly (such as with resource-constrained robots) or inefficient (for example, submersibles that need to surface), especially when navigating in environm... | {
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2411.08284 | Dynamic Thresholding Algorithm with Memory for Linear Inverse Problems | [
"cs.IT",
"cs.NA",
"math.IT",
"math.NA"
] | The relaxed optimal $k$-thresholding pursuit (ROTP) is a recent algorithm for linear inverse problems. This algorithm is based on the optimal $k$-thresholding technique which performs vector thresholding and error metric reduction simultaneously. Although ROTP can be used to solve small to medium-sized linear inverse p... | {
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2411.08286 | Hashing for Protein Structure Similarity Search | [
"cs.LG",
"cs.AI",
"q-bio.QM"
] | Protein structure similarity search (PSSS), which tries to search proteins with similar structures, plays a crucial role across diverse domains from drug design to protein function prediction and molecular evolution. Traditional alignment-based PSSS methods, which directly calculate alignment on the protein structures,... | {
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2411.08290 | RESOLVE: Relational Reasoning with Symbolic and Object-Level Features
Using Vector Symbolic Processing | [
"cs.AI",
"cs.LG"
] | Modern transformer-based encoder-decoder architectures struggle with reasoning tasks due to their inability to effectively extract relational information between input objects (data/tokens). Recent work introduced the Abstractor module, embedded between transformer layers, to address this gap. However, the Abstractor l... | {
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2411.08291 | Restoration algorithms and system performance evaluation for active
imagers | [
"cs.CV"
] | This paper deals with two fields related to active imaging system. First, we begin to explore image processing algorithms to restore the artefacts like speckle, scintillation and image dancing caused by atmospheric turbulence. Next, we examine how to evaluate the performance of this kind of systems. To do this task, we... | {
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2411.08292 | Noisy image decomposition: a new structure, texture and noise model
based on local adaptivity | [
"cs.CV",
"eess.IV",
"math.FA"
] | These last few years, image decomposition algorithms have been proposed to split an image into two parts: the structures and the textures. These algorithms are not adapted to the case of noisy images because the textures are corrupted by noise. In this paper, we propose a new model which decomposes an image into three ... | {
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2411.08293 | Choix d'un espace de repr\'esentation image adapt\'e \`a la d\'etection
de r\'eseaux routiers | [
"cs.CV",
"eess.IV",
"math.FA"
] | These last years, algorithms allowing to decompose an image into its structures and textures components have emerged. In this paper, we present an application of this type of decomposition to the problem road network detection in aerial or satelite imagery. The algorithmic procedure involves the image decomposition (us... | {
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2411.08297 | TowerDebias: A Novel Debiasing Method based on the Tower Property | [
"cs.LG",
"cs.AI",
"math.PR",
"stat.AP",
"stat.ML"
] | Decision-making processes have increasingly come to rely on sophisticated machine learning tools, raising concerns about the fairness of their predictions with respect to any sensitive groups. The widespread use of commercial black-box machine learning models necessitates careful consideration of their legal and ethica... | {
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2411.08299 | DNN Task Assignment in UAV Networks: A Generative AI Enhanced
Multi-Agent Reinforcement Learning Approach | [
"cs.AI"
] | Unmanned Aerial Vehicles (UAVs) possess high mobility and flexible deployment capabilities, prompting the development of UAVs for various application scenarios within the Internet of Things (IoT). The unique capabilities of UAVs give rise to increasingly critical and complex tasks in uncertain and potentially harsh env... | {
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2411.08302 | R3HF: Reward Redistribution for Enhancing Reinforcement Learning from
Human Feedback | [
"cs.CL",
"cs.AI"
] | Reinforcement learning from human feedback (RLHF) provides a paradigm for aligning large language models (LLMs) with human preferences. This involves the initial training of a reward model based on pairwise human feedback. The reward model is subsequently utilized in reinforcement learning to assess the scores of each ... | {
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2411.08305 | Robust Divergence Learning for Missing-Modality Segmentation | [
"eess.IV",
"cs.CV"
] | Multimodal Magnetic Resonance Imaging (MRI) provides essential complementary information for analyzing brain tumor subregions. While methods using four common MRI modalities for automatic segmentation have shown success, they often face challenges with missing modalities due to image quality issues, inconsistent protoc... | {
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2411.08306 | SDDBench: A Benchmark for Synthesizable Drug Design | [
"cs.LG",
"q-bio.QM"
] | A significant challenge in wet lab experiments with current drug design generative models is the trade-off between pharmacological properties and synthesizability. Molecules predicted to have highly desirable properties are often difficult to synthesize, while those that are easily synthesizable tend to exhibit less fa... | {
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2411.08307 | PerceiverS: A Multi-Scale Perceiver with Effective Segmentation for
Long-Term Expressive Symbolic Music Generation | [
"cs.AI",
"cs.MM",
"cs.SD",
"eess.AS"
] | AI-based music generation has progressed significantly in recent years. However, creating symbolic music that is both long-structured and expressive remains a considerable challenge. In this paper, we propose PerceiverS (Segmentation and Scale), a novel architecture designed to address this issue by leveraging both Eff... | {
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2411.08314 | Conditional Variable Flow Matching: Transforming Conditional Densities
with Amortized Conditional Optimal Transport | [
"cs.LG"
] | Forecasting stochastic nonlinear dynamical systems under the influence of conditioning variables is a fundamental challenge repeatedly encountered across the biological and physical sciences. While flow-based models can impressively predict the temporal evolution of probability distributions representing possible outco... | {
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2411.08320 | Responsible AI in Construction Safety: Systematic Evaluation of Large
Language Models and Prompt Engineering | [
"cs.AI"
] | Construction remains one of the most hazardous sectors. Recent advancements in AI, particularly Large Language Models (LLMs), offer promising opportunities for enhancing workplace safety. However, responsible integration of LLMs requires systematic evaluation, as deploying them without understanding their capabilities ... | {
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2411.08323 | Efficient Trajectory Generation in 3D Environments with Multi-Level Map
Construction | [
"cs.RO"
] | We propose a robust and efficient framework to generate global trajectories for ground robots in complex 3D environments. The proposed method takes point cloud as input and efficiently constructs a multi-level map using triangular patches as the basic elements. A kinematic path search is adopted on the patches, where m... | {
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2411.08324 | Are LLMs Prescient? A Continuous Evaluation using Daily News as the
Oracle | [
"cs.CL",
"cs.AI",
"cs.LG"
] | Many existing evaluation benchmarks for Large Language Models (LLMs) quickly become outdated due to the emergence of new models and training data. These benchmarks also fall short in assessing how LLM performance changes over time, as they consist of static questions without a temporal dimension. To address these limit... | {
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2411.08326 | Neural Conjugate Flows: Physics-informed architectures with flow
structure | [
"cs.LG",
"cs.NA",
"math.NA"
] | We introduce Neural Conjugate Flows (NCF), a class of neural network architectures equipped with exact flow structure. By leveraging topological conjugation, we prove that these networks are not only naturally isomorphic to a continuous group, but are also universal approximators for flows of ordinary differential equa... | {
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2411.08328 | Motion Control for Enhanced Complex Action Video Generation | [
"cs.CV"
] | Existing text-to-video (T2V) models often struggle with generating videos with sufficiently pronounced or complex actions. A key limitation lies in the text prompt's inability to precisely convey intricate motion details. To address this, we propose a novel framework, MVideo, designed to produce long-duration videos wi... | {
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2411.08329 | Neural Network Certification Informed Power System Transient Stability
Preventive Control with Renewable Energy | [
"eess.SY",
"cs.SY"
] | Existing machine learning-based surrogate modeling methods for transient stability constrained-optimal power flow (TSC-OPF) lack certifications in the presence of unseen disturbances or uncertainties. This may lead to divergence of TSC-OPF or insecure control strategies. This paper proposes a neural network certificati... | {
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2411.08332 | Learning-Augmented Algorithms for Online Concave Packing and Convex
Covering Problems | [
"cs.DS",
"cs.LG",
"math.OC"
] | Learning-augmented algorithms have been extensively studied across the computer science community in the recent years, driven by advances in machine learning predictors, which can provide additional information to augment classical algorithms. Such predictions are especially powerful in the context of online problems, ... | {
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2411.08333 | SASE: A Searching Architecture for Squeeze and Excitation Operations | [
"cs.CV"
] | In the past few years, channel-wise and spatial-wise attention blocks have been widely adopted as supplementary modules in deep neural networks, enhancing network representational abilities while introducing low complexity. Most attention modules follow a squeeze-and-excitation paradigm. However, to design such attenti... | {
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2411.08334 | MIRe: Enhancing Multimodal Queries Representation via Fusion-Free
Modality Interaction for Multimodal Retrieval | [
"cs.CV",
"cs.AI",
"cs.IR",
"cs.MM"
] | Recent multimodal retrieval methods have endowed text-based retrievers with multimodal capabilities by utilizing pre-training strategies for visual-text alignment. They often directly fuse the two modalities for cross-reference during the alignment to understand multimodal queries. However, existing methods often overl... | {
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2411.08335 | DEEGITS: Deep Learning based Framework for Measuring Heterogenous
Traffic State in Challenging Traffic Scenarios | [
"cs.CV",
"cs.AI"
] | This paper presents DEEGITS (Deep Learning Based Heterogeneous Traffic State Measurement), a comprehensive framework that leverages state-of-the-art convolutional neural network (CNN) techniques to accurately and rapidly detect vehicles and pedestrians, as well as to measure traffic states in challenging scenarios (i.e... | {
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2411.08340 | DyConfidMatch: Dynamic Thresholding and Re-sampling for 3D
Semi-supervised Learning | [
"cs.CV"
] | Semi-supervised learning (SSL) leverages limited labeled and abundant unlabeled data but often faces challenges with data imbalance, especially in 3D contexts. This study investigates class-level confidence as an indicator of learning status in 3D SSL, proposing a novel method that utilizes dynamic thresholding to bett... | {
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2411.08341 | Generative AI for Data Augmentation in Wireless Networks: Analysis,
Applications, and Case Study | [
"cs.NI",
"cs.AI"
] | Data augmentation is a powerful technique to mitigate data scarcity. However, owing to fundamental differences in wireless data structures, traditional data augmentation techniques may not be suitable for wireless data. Fortunately, Generative Artificial Intelligence (GenAI) can be an effective alternative to wireless ... | {
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2411.08344 | Bangla Grammatical Error Detection Leveraging Transformer-based Token
Classification | [
"cs.CL",
"cs.LG"
] | Bangla is the seventh most spoken language by a total number of speakers in the world, and yet the development of an automated grammar checker in this language is an understudied problem. Bangla grammatical error detection is a task of detecting sub-strings of a Bangla text that contain grammatical, punctuation, or spe... | {
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2411.08347 | A Chinese Multi-label Affective Computing Dataset Based on Social Media
Network Users | [
"cs.CV",
"cs.AI",
"cs.CL",
"cs.CY"
] | Emotion and personality are central elements in understanding human psychological states. Emotions reflect an individual subjective experiences, while personality reveals relatively stable behavioral and cognitive patterns. Existing affective computing datasets often annotate emotion and personality traits separately, ... | {
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2411.08348 | Refining Translations with LLMs: A Constraint-Aware Iterative Prompting
Approach | [
"cs.CL"
] | Large language models (LLMs) have demonstrated remarkable proficiency in machine translation (MT), even without specific training on the languages in question. However, translating rare words in low-resource or domain-specific contexts remains challenging for LLMs. To address this issue, we propose a multi-step prompt ... | {
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2411.08355 | Optimal Decentralized Smoothed Online Convex Optimization | [
"math.OC",
"cs.DS",
"cs.LG"
] | We study the multi-agent Smoothed Online Convex Optimization (SOCO) problem, where $N$ agents interact through a communication graph. In each round, each agent $i$ receives a strongly convex hitting cost function $f^i_t$ in an online fashion and selects an action $x^i_t \in \mathbb{R}^d$. The objective is to minimize t... | {
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2411.08360 | Coverage Analysis for Digital Cousin Selection -- Improving
Multi-Environment Q-Learning | [
"cs.LG",
"eess.SP"
] | Q-learning is widely employed for optimizing various large-dimensional networks with unknown system dynamics. Recent advancements include multi-environment mixed Q-learning (MEMQ) algorithms, which utilize multiple independent Q-learning algorithms across multiple, structurally related but distinct environments and out... | {
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2411.08367 | Surprisingly Popular Voting for Concentric Rank-Order Models | [
"cs.GT",
"cs.AI",
"cs.LG"
] | An important problem on social information sites is the recovery of ground truth from individual reports when the experts are in the minority. The wisdom of the crowd, i.e. the collective opinion of a group of individuals fails in such a scenario. However, the surprisingly popular (SP) algorithm~\cite{prelec2017solutio... | {
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2411.08370 | A Fuzzy Reinforcement LSTM-based Long-term Prediction Model for Fault
Conditions in Nuclear Power Plants | [
"cs.AI"
] | Early fault detection and timely maintenance scheduling can significantly mitigate operational risks in NPPs and enhance the reliability of operator decision-making. Therefore, it is necessary to develop an efficient Prognostics and Health Management (PHM) multi-step prediction model for predicting of system health sta... | {
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2411.08371 | Multiscale Graph Construction Using Non-local Cluster Features | [
"cs.CV",
"eess.SP"
] | This paper presents a multiscale graph construction method using both graph and signal features. Multiscale graph is a hierarchical representation of the graph, where a node at each level indicates a cluster in a finer resolution. To obtain the hierarchical clusters, existing methods often use graph clustering; however... | {
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2411.08373 | DG-SLAM: Robust Dynamic Gaussian Splatting SLAM with Hybrid Pose
Optimization | [
"cs.RO"
] | Achieving robust and precise pose estimation in dynamic scenes is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent advancements integrating Gaussian Splatting into SLAM systems have proven effective in creating high-quality renderings using explicit 3D Gaussian models, sig... | {
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2411.08374 | Federated Graph Learning with Graphless Clients | [
"cs.LG",
"cs.DC"
] | Federated Graph Learning (FGL) is tasked with training machine learning models, such as Graph Neural Networks (GNNs), for multiple clients, each with its own graph data. Existing methods usually assume that each client has both node features and graph structure of its graph data. In real-world scenarios, however, there... | {
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2411.08375 | Developing an Effective Training Dataset to Enhance the Performance of
AI-based Speaker Separation Systems | [
"cs.SD",
"cs.AI",
"eess.AS"
] | This paper addresses the challenge of speaker separation, which remains an active research topic despite the promising results achieved in recent years. These results, however, often degrade in real recording conditions due to the presence of noise, echo, and other interferences. This is because neural models are typic... | {
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2411.08378 | Physics Informed Distillation for Diffusion Models | [
"cs.LG",
"cs.AI"
] | Diffusion models have recently emerged as a potent tool in generative modeling. However, their inherent iterative nature often results in sluggish image generation due to the requirement for multiple model evaluations. Recent progress has unveiled the intrinsic link between diffusion models and Probability Flow Ordinar... | {
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2411.08380 | EgoVid-5M: A Large-Scale Video-Action Dataset for Egocentric Video
Generation | [
"cs.CV"
] | Video generation has emerged as a promising tool for world simulation, leveraging visual data to replicate real-world environments. Within this context, egocentric video generation, which centers on the human perspective, holds significant potential for enhancing applications in virtual reality, augmented reality, and ... | {
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2411.08384 | Interpretable Syntactic Representations Enable Hierarchical Word Vectors | [
"cs.CL",
"cs.LG"
] | The distributed representations currently used are dense and uninterpretable, leading to interpretations that themselves are relative, overcomplete, and hard to interpret. We propose a method that transforms these word vectors into reduced syntactic representations. The resulting representations are compact and interpr... | {
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2411.08389 | Integrative Wrapping System for a Dual-Arm Humanoid Robot | [
"cs.RO"
] | Flexible object manipulation of paper and cloth is a major research challenge in robot manipulation. Although there have been efforts to develop hardware that enables specific actions and to realize a single action of paper folding using sim-to-real and learning, there have been few proposals for humanoid robots and sy... | {
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2411.08392 | RLInspect: An Interactive Visual Approach to Assess Reinforcement
Learning Algorithm | [
"cs.AI"
] | Reinforcement Learning (RL) is a rapidly growing area of machine learning that finds its application in a broad range of domains, from finance and healthcare to robotics and gaming. Compared to other machine learning techniques, RL agents learn from their own experiences using trial and error, and improve their perform... | {
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2411.08395 | MambaXCTrack: Mamba-based Tracker with SSM Cross-correlation and Motion
Prompt for Ultrasound Needle Tracking | [
"cs.CV",
"cs.RO"
] | Ultrasound (US)-guided needle insertion is widely employed in percutaneous interventions. However, providing feedback on the needle tip position via US image presents challenges due to noise, artifacts, and the thin imaging plane of US, which degrades needle features and leads to intermittent tip visibility. In this pa... | {
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2411.08397 | CLaSP: Learning Concepts for Time-Series Signals from Natural Language
Supervision | [
"cs.CL",
"cs.LG"
] | This paper proposes a foundation model called "CLaSP" that can search time series signals using natural language that describes the characteristics of the signals as queries. Previous efforts to represent time series signal data in natural language have had challenges in designing a conventional class of time series si... | {
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2411.08400 | BAMAX: Backtrack Assisted Multi-Agent Exploration using Reinforcement
Learning | [
"cs.RO",
"cs.AI"
] | Autonomous robots collaboratively exploring an unknown environment is still an open problem. The problem has its roots in coordination among non-stationary agents, each with only a partial view of information. The problem is compounded when the multiple robots must completely explore the environment. In this paper, we ... | {
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2411.08402 | V2X-R: Cooperative LiDAR-4D Radar Fusion for 3D Object Detection with
Denoising Diffusion | [
"cs.CV"
] | Current Vehicle-to-Everything (V2X) systems have significantly enhanced 3D object detection using LiDAR and camera data. However, these methods suffer from performance degradation in adverse weather conditions. The weatherrobust 4D radar provides Doppler and additional geometric information, raising the possibility of ... | {
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2411.08404 | Quantifying Qualitative Insights: Leveraging LLMs to Market Predict | [
"q-fin.CP",
"cs.LG"
] | Recent advancements in Large Language Models (LLMs) have the potential to transform financial analytics by integrating numerical and textual data. However, challenges such as insufficient context when fusing multimodal information and the difficulty in measuring the utility of qualitative outputs, which LLMs generate a... | {
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2411.08405 | An Ising Machine Formulation for Design Updates in Topology Optimization
of Flow Channels | [
"cs.CE",
"math.OC"
] | Topology optimization is an essential tool in computational engineering, for example, to improve the design and efficiency of flow channels. At the same time, Ising machines, including digital or quantum annealers, have been used as efficient solvers for combinatorial optimization problems. Beyond combinatorial optimiz... | {
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2411.08409 | DiVR: incorporating context from diverse VR scenes for human trajectory
prediction | [
"cs.AI",
"cs.MM"
] | Virtual environments provide a rich and controlled setting for collecting detailed data on human behavior, offering unique opportunities for predicting human trajectories in dynamic scenes. However, most existing approaches have overlooked the potential of these environments, focusing instead on static contexts without... | {
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2411.08410 | The VLLM Safety Paradox: Dual Ease in Jailbreak Attack and Defense | [
"cs.CR",
"cs.CV"
] | The vulnerability of Vision Large Language Models (VLLMs) to jailbreak attacks appears as no surprise. However, recent defense mechanisms against these attacks have reached near-saturation performance on benchmarks, often with minimal effort. This simultaneous high performance in both attack and defense presents a perp... | {
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2411.08411 | Modeling and Optimization for Rotatable Antenna Enabled Wireless
Communication | [
"cs.IT",
"eess.SP",
"math.IT"
] | Fluid antenna system (FAS)/movable antenna (MA) has emerged as a promising technology to fully exploit the spatial degrees of freedom (DoFs). In this paper, we propose a new rotatable antenna (RA) model, as a simplified implementation of six-dimensional movable antenna (6DMA), to improve the performance of wireless com... | {
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2411.08413 | Inference-Aware State Reconstruction for Industrial Metaverse under
Synchronous/Asynchronous Short-Packet Transmission | [
"eess.SY",
"cs.SY"
] | We consider a real-time state reconstruction system for industrial metaverse. The time-varying physical process states in real space are captured by multiple sensors via wireless links, and then reconstructed in virtual space. In this paper, we use the spatial-temporal correlation of the sensor data of interest to infe... | {
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2411.08414 | Material Property Prediction with Element Attribute Knowledge Graphs and
Multimodal Representation Learning | [
"cs.LG",
"cond-mat.mtrl-sci",
"cs.AI"
] | Machine learning has become a crucial tool for predicting the properties of crystalline materials. However, existing methods primarily represent material information by constructing multi-edge graphs of crystal structures, often overlooking the chemical and physical properties of elements (such as atomic radius, electr... | {
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2411.08418 | Enhanced Classroom Dialogue Sequences Analysis with a Hybrid AI Agent:
Merging Expert Rule-Base with Large Language Models | [
"cs.AI"
] | Classroom dialogue plays a crucial role in fostering student engagement and deeper learning. However, analysing dialogue sequences has traditionally relied on either theoretical frameworks or empirical descriptions of practice, with limited integration between the two. This study addresses this gap by developing a comp... | {
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2411.08424 | A Heterogeneous Graph Neural Network Fusing Functional and Structural
Connectivity for MCI Diagnosis | [
"cs.CV",
"cs.AI"
] | Brain connectivity alternations associated with brain disorders have been widely reported in resting-state functional imaging (rs-fMRI) and diffusion tensor imaging (DTI). While many dual-modal fusion methods based on graph neural networks (GNNs) have been proposed, they generally follow homogenous fusion ways ignoring... | {
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2411.08425 | Properties of fairness measures in the context of varying class
imbalance and protected group ratios | [
"cs.LG",
"cs.CY"
] | Society is increasingly relying on predictive models in fields like criminal justice, credit risk management, or hiring. To prevent such automated systems from discriminating against people belonging to certain groups, fairness measures have become a crucial component in socially relevant applications of machine learni... | {
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2411.08432 | One STEP at a time: Language Agents are Stepwise Planners | [
"cs.CL",
"cs.AI",
"cs.LG"
] | Language agents have shown promising adaptability in dynamic environments to perform complex tasks. However, despite the versatile knowledge embedded in large language models, these agents still fall short when it comes to tasks that require planning. We introduce STEP, a novel framework designed to efficiently learn f... | {
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2411.08433 | 3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter | [
"cs.RO",
"cs.AI"
] | 3D Multi-Object Tracking (MOT), a fundamental component of environmental perception, is essential for intelligent systems like autonomous driving and robotic sensing. Although Tracking-by-Detection frameworks have demonstrated excellent performance in recent years, their application in real-world scenarios faces signif... | {
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2411.08436 | Robust performance for switched systems with constrained switching and
its application to weakly hard real-time control systems | [
"eess.SY",
"cs.SY",
"math.OC"
] | Many cyber-physical systems can naturally be formulated as switched systems with constrained switching. This includes systems where one of the signals in the feedback loop may be lost. Possible sources for losses are shared or unreliable communication media in networked control systems, or signals which are discarded, ... | {
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2411.08437 | Evolutionary Algorithm with Detection Region Method for Constrained
Multi-Objective Problems with Binary Constraints | [
"cs.NE"
] | Solving constrained multi-objective optimization problems (CMOPs) is a challenging task. While many practical algorithms have been developed to tackle CMOPs, real-world scenarios often present cases where the constraint functions are unknown or unquantifiable, resulting in only binary outcomes (feasible or infeasible).... | {
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2411.08438 | Towards Optimizing a Retrieval Augmented Generation using Large Language
Model on Academic Data | [
"cs.AI"
] | Given the growing trend of many organizations integrating Retrieval Augmented Generation (RAG) into their operations, we assess RAG on domain-specific data and test state-of-the-art models across various optimization techniques. We incorporate four optimizations; Multi-Query, Child-Parent-Retriever, Ensemble Retriever,... | {
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} |
2411.08443 | Machine Unlearning on Pre-trained Models by Residual Feature Alignment
Using LoRA | [
"cs.LG",
"cs.CV"
] | Machine unlearning is new emerged technology that removes a subset of the training data from a trained model without affecting the model performance on the remaining data. This topic is becoming increasingly important in protecting user privacy and eliminating harmful or outdated data. The key challenge lies in effecti... | {
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} |
2411.08447 | Learning Dynamic Cognitive Map with Autonomous Navigation | [
"cs.RO",
"cs.AI",
"cs.LG"
] | Inspired by animal navigation strategies, we introduce a novel computational model to navigate and map a space rooted in biologically inspired principles. Animals exhibit extraordinary navigation prowess, harnessing memory, imagination, and strategic decision-making to traverse complex and aliased environments adeptly.... | {
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} |
2411.08449 | Towards Evaluating Large Language Models for Graph Query Generation | [
"cs.ET",
"cs.CL"
] | Large Language Models (LLMs) are revolutionizing the landscape of Generative Artificial Intelligence (GenAI), with innovative LLM-backed solutions emerging rapidly. However, when applied to database technologies, specifically query generation for graph databases and Knowledge Graphs (KGs), LLMs still face significant c... | {
"Other": 1,
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} |
2411.08451 | AD-DINO: Attention-Dynamic DINO for Distance-Aware Embodied Reference
Understanding | [
"cs.CV"
] | Embodied reference understanding is crucial for intelligent agents to predict referents based on human intention through gesture signals and language descriptions. This paper introduces the Attention-Dynamic DINO, a novel framework designed to mitigate misinterpretations of pointing gestures across various interaction ... | {
"Other": 0,
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} |
2411.08453 | Biomass phenotyping of oilseed rape through UAV multi-view oblique
imaging with 3DGS and SAM model | [
"cs.CV"
] | Biomass estimation of oilseed rape is crucial for optimizing crop productivity and breeding strategies. While UAV-based imaging has advanced high-throughput phenotyping, current methods often rely on orthophoto images, which struggle with overlapping leaves and incomplete structural information in complex field environ... | {
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} |
2411.08460 | Trap-MID: Trapdoor-based Defense against Model Inversion Attacks | [
"cs.CR",
"cs.AI",
"cs.CV",
"cs.LG"
] | Model Inversion (MI) attacks pose a significant threat to the privacy of Deep Neural Networks by recovering training data distribution from well-trained models. While existing defenses often rely on regularization techniques to reduce information leakage, they remain vulnerable to recent attacks. In this paper, we prop... | {
"Other": 0,
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} |
2411.08463 | Symbolic-AI-Fusion Deep Learning (SAIF-DL): Encoding Knowledge into
Training with Answer Set Programming Loss Penalties by a Novel Loss Function
Approach | [
"cs.AI",
"cs.ET"
] | This paper presents a hybrid methodology that enhances the training process of deep learning (DL) models by embedding domain expert knowledge using ontologies and answer set programming (ASP). By integrating these symbolic AI methods, we encode domain-specific constraints, rules, and logical reasoning directly into the... | {
"Other": 1,
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} |
2411.08464 | Crystal Structure Generation Based On Material Properties | [
"cs.AI",
"cond-mat.mtrl-sci"
] | The discovery of new materials is very important to the field of materials science. When researchers explore new materials, they often have expected performance requirements for their crystal structure. In recent years, data-driven methods have made great progress in the direction plane of crystal structure generation,... | {
"Other": 0,
"cs.AI": 1,
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} |
2411.08466 | Can MLLMs Guide Weakly-Supervised Temporal Action Localization Tasks? | [
"cs.CV"
] | Recent breakthroughs in Multimodal Large Language Models (MLLMs) have gained significant recognition within the deep learning community, where the fusion of the Video Foundation Models (VFMs) and Large Language Models(LLMs) has proven instrumental in constructing robust video understanding systems, effectively surmount... | {
"Other": 0,
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} |
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