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272770204 | 2409.13345 | 2024-09-20 | A Novel Adaptive Fine-Tuning Algorithm for Multimodal Models: Self-Optimizing Classification and Selection of High-Quality Datasets in Remote Sensing | We propose an adaptive fine-tuning algorithm for multimodal large models. The core steps of this algorithm involve two stages of truncation. First, the vast amount of data is projected into a semantic vector space, and the MiniBatchKMeans algorithm is used for automated clustering. This classification ensures that the ... | [
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272831740 | 2409.15376 | 2024-09-20 | ControlMath: Controllable Data Generation Promotes Math Generalist Models | Utilizing large language models (LLMs) for data augmentation has yielded encouraging results in mathematical reasoning. However, these approaches face constraints in problem diversity, potentially restricting them to in-domain/distribution data generation. To this end, we propose ControlMath, an iterative method involv... | [
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272770605 | 2409.13573 | 2024-09-20 | Human-Robot Cooperative Distribution Coupling for Hamiltonian-Constrained Social Navigation | Navigating in human-filled public spaces is a critical challenge for deploying autonomous robots in real-world environments. This paper introduces NaviDIFF, a novel Hamiltonian-constrained socially-aware navigation framework designed to address the complexities of human-robot interaction and socially-aware path plannin... | [
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272770298 | 2409.13401 | 2024-09-20 | PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images | Segment Anything Model (SAM) is an advanced foundational model for image segmentation, which is gradually being applied to remote sensing images (RSIs). Due to the domain gap between RSIs and natural images, traditional methods typically use SAM as a source pre-trained model and fine-tune it with fully supervised masks... | [
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272770249 | 2409.13310 | 2024-09-20 | MeMoir: A Software-Driven Covert Channel based on Memory Usage | Covert channel attacks have been continuously studied as severe threats to modern computing systems. Software-based covert channels are a typically hard-to-detect branch of these attacks, since they leverage virtual resources to establish illegitimate communication between malicious actors. In this work, we present MeM... | [
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272770572 | 2409.13312 | 2024-09-20 | GAProtoNet: A Multi-head Graph Attention-based Prototypical Network for Interpretable Text Classification | Pretrained transformer-based Language Models (LMs) are well-known for their ability to achieve significant improvement on text classification tasks with their powerful word embeddings, but their black-box nature, which leads to a lack of interpretability, has been a major concern. In this work, we introduce GAProtoNet,... | [
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272770471 | 2409.13416 | 2024-09-20 | Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting | Accurate segmentation of Multiple Sclerosis (MS) lesions in longitudinal MRI scans is crucial for monitoring disease progression and treatment efficacy. Although changes across time are taken into account when assessing images in clinical practice, most existing deep learning methods treat scans from different timepoin... | [
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273233421 | 2410.07122 | 2024-09-20 | End-Cloud Collaboration Framework for Advanced AI Customer Service in E-commerce | In recent years, the e-commerce industry has seen a rapid increase in the demand for advanced AI-driven customer service solutions. Traditional cloud-based models face limitations in terms of latency, personalized services, and privacy concerns. Furthermore, end devices often lack the computational resources to deploy ... | [
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272770786 | 2409.13544 | 2024-09-20 | Graph Similarity Regularized Softmax for Semi-Supervised Node Classification | Graph Neural Networks (GNNs) are powerful deep learning models designed for graph-structured data, demonstrating effectiveness across a wide range of applications.The softmax function is the most commonly used classifier for semi-supervised node classification. However, the softmax function lacks spatial information of... | [
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272770159 | 2409.13678 | 2024-09-20 | SoloParkour: Constrained Reinforcement Learning for Visual Locomotion from Privileged Experience | Parkour poses a significant challenge for legged robots, requiring navigation through complex environments with agility and precision based on limited sensory inputs. In this work, we introduce a novel method for training end-to-end visual policies, from depth pixels to robot control commands, to achieve agile and safe... | [
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272770459 | 2409.13203 | 2024-09-20 | Neural-Symbolic Collaborative Distillation: Advancing Small Language Models for Complex Reasoning Tasks | In this paper, we propose $\textbf{Ne}$ural-$\textbf{Sy}$mbolic $\textbf{C}$ollaborative $\textbf{D}$istillation ($\textbf{NesyCD}$), a novel knowledge distillation method for learning the complex reasoning abilities of Large Language Models (LLMs, e.g., \textgreater 13B). We argue that complex reasoning tasks are diff... | [
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273186516 | 2410.03686 | 2024-09-20 | LCM: Log Conformal Maps for Robust Representation Learning to Mitigate Perspective Distortion | Perspective distortion (PD) leads to substantial alterations in the shape, size, orientation, angles, and spatial relationships of visual elements in images. Accurately determining camera intrinsic and extrinsic parameters is challenging, making it hard to synthesize perspective distortion effectively. The current dist... | [
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272770357 | 2409.13268 | 2024-09-20 | JoyHallo: Digital human model for Mandarin | In audio-driven video generation, creating Mandarin videos presents significant challenges. Collecting comprehensive Mandarin datasets is difficult, and the complex lip movements in Mandarin further complicate model training compared to English. In this study, we collected 29 hours of Mandarin speech video from JD Heal... | [
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272770336 | 2409.13580 | 2024-09-20 | Lyapunov-guided Deep Reinforcement Learning for Semantic-aware AoI Minimization in UAV-assisted Wireless Networks | This paper investigates an unmanned aerial vehicle (UAV)-assisted semantic network where the ground users (GUs) periodically capture and upload the sensing information to a base station (BS) via UAVs' relaying. Both the GUs and the UAVs can extract semantic information from large-size raw data and transmit it to the BS... | [
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272770356 | 2409.13517 | 2024-09-20 | Efficient Entanglement Routing for Satellite-Aerial-Terrestrial Quantum Networks | In the era of 6G and beyond, space-aerial-terrestrial quantum networks (SATQNs) are shaping the future of the global-scale quantum Internet. This paper investigates the collaboration among satellite, aerial, and terrestrial quantum networks to efficiently transmit high-fidelity quantum entanglements over long distances... | [
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272827477 | 2409.13878 | 2024-09-20 | Cross-Domain Knowledge Transfer for Underwater Acoustic Classification Using Pre-trained Models | Transfer learning is commonly employed to leverage large, pre-trained models and perform fine-tuning for downstream tasks. The most prevalent pre-trained models are initially trained using ImageNet. However, their ability to generalize can vary across different data modalities. This study compares pre-trained Audio Neu... | [
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272770175 | 2409.13609 | 2024-09-20 | MaPPER: Multimodal Prior-guided Parameter Efficient Tuning for Referring Expression Comprehension | Referring Expression Comprehension (REC), which aims to ground a local visual region via natural language, is a task that heavily relies on multimodal alignment. Most existing methods utilize powerful pre-trained models to transfer visual/linguistic knowledge by full fine-tuning. However, full fine-tuning the entire ba... | [
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272770225 | 2409.13390 | 2024-09-20 | Hydrogen under Pressure as a Benchmark for Machine-Learning Interatomic Potentials | Machine-learning interatomic potentials (MLPs) are fast, data-driven surrogate models of atomistic systems' potential energy surfaces that can accelerate ab-initio molecular dynamics (MD) simulations by several orders of magnitude. The performance of MLPs is commonly measured as the prediction error in energies and for... | [
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272827980 | 2409.13832 | 2024-09-20 | GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks | The scarcity of high-quality and multi-task singing datasets significantly hinders the development of diverse controllable and personalized singing tasks, as existing singing datasets suffer from low quality, limited diversity of languages and singers, absence of multi-technique information and realistic music scores, ... | [
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272827445 | 2409.13926 | 2024-09-20 | SpaceBlender: Creating Context-Rich Collaborative Spaces Through Generative 3D Scene Blending | There is increased interest in using generative AI to create 3D spaces for Virtual Reality (VR) applications. However, today's models produce artificial environments, falling short of supporting collaborative tasks that benefit from incorporating the user's physical context. To generate environments that support VR tel... | [
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272770139 | 2409.13484 | 2024-09-20 | 'Since Lawyers are Males..': Examining Implicit Gender Bias in Hindi Language Generation by LLMs | Large Language Models (LLMs) are increasingly being used to generate text across various languages, for tasks such as translation, customer support, and education. Despite these advancements, LLMs show notable gender biases in English, which become even more pronounced when generating content in relatively underreprese... | [
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272770382 | 2409.13286 | 2024-09-20 | Generative Learning Powered Probing Beam Optimization for Cell-Free Hybrid Beamforming | Probing beam measurement (PBM)-based hybrid beamforming provides a feasible solution for cell-free MIMO. In this letter, we propose a novel probing beam optimization framework where three collaborative modules respectively realize PBM augmentation, sum-rate prediction and probing beam optimization. Specifically, the PB... | [
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272828115 | 2409.14083 | 2024-09-21 | SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Information | Large Vision-Language Models (LVLMs) have become pivotal at the intersection of computer vision and natural language processing. However, the full potential of LVLMs Retrieval-Augmented Generation (RAG) capabilities remains underutilized. Existing works either focus solely on the text modality or are limited to specifi... | [
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272827050 | 2409.13977 | 2024-09-21 | Improving 3D Semi-supervised Learning by Effectively Utilizing All Unlabelled Data | Semi-supervised learning (SSL) has shown its effectiveness in learning effective 3D representation from a small amount of labelled data while utilizing large unlabelled data. Traditional semi-supervised approaches rely on the fundamental concept of predicting pseudo-labels for unlabelled data and incorporating them int... | [
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272827986 | 2409.13968 | 2024-09-21 | LADICA: A Large Shared Display Interface for Generative AI Cognitive Assistance in Co-Located Team Collaboration | Large shared displays, such as digital whiteboards, are useful for supporting co-located team collaborations by helping members perform cognitive tasks such as brainstorming, organizing ideas, and making comparisons. While recent advancement in Large Language Models (LLMs) has catalyzed AI support for these displays, m... | [
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272827643 | 2409.14131 | 2024-09-21 | Are Music Foundation Models Better at Singing Voice Deepfake Detection? Far-Better Fuse them with Speech Foundation Models | In this study, for the first time, we extensively investigate whether music foundation models (MFMs) or speech foundation models (SFMs) work better for singing voice deepfake detection (SVDD), which has recently attracted attention in the research community. For this, we perform a comprehensive comparative study of sta... | [
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272827003 | 2409.14215 | 2024-09-21 | @Bench: Benchmarking Vision-Language Models for Human-centered Assistive Technology | As Vision-Language Models (VLMs) advance, human-centered Assistive Technologies (ATs) for helping People with Visual Impairments (PVIs) are evolving into generalists, capable of performing multiple tasks simultaneously. However, benchmarking VLMs for ATs remains under-explored. To bridge this gap, we first create a nov... | [
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272826722 | 2409.14031 | 2024-09-21 | Maximum-Likelihood Estimation Based on Diffusion Model For Wireless Communications | Generative Artificial Intelligence (GenAI) models, with their powerful feature learning capabilities, have been applied in many fields. In mobile wireless communications, GenAI can dynamically optimize the network to enhance the user experience. Especially in signal detection and channel estimation tasks, due to digita... | [
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272827856 | 2409.13972 | 2024-09-21 | Can Language Model Understand Word Semantics as A Chatbot? An Empirical Study of Language Model Internal External Mismatch | Current common interactions with language models is through full inference. This approach may not necessarily align with the model's internal knowledge. Studies show discrepancies between prompts and internal representations. Most focus on sentence understanding. We study the discrepancy of word semantics understanding... | [
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272827375 | 2409.14000 | 2024-09-21 | Graph Neural Network Framework for Sentiment Analysis Using Syntactic Feature | Amidst the swift evolution of social media platforms and e-commerce ecosystems, the domain of opinion mining has surged as a pivotal area of exploration within natural language processing. A specialized segment within this field focuses on extracting nuanced evaluations tied to particular elements within textual contex... | [
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272831802 | 2409.15381 | 2024-09-21 | Adversarial Attacks on Parts of Speech: An Empirical Study in Text-to-Image Generation | Recent studies show that text-to-image (T2I) models are vulnerable to adversarial attacks, especially with noun perturbations in text prompts. In this study, we investigate the impact of adversarial attacks on different POS tags within text prompts on the images generated by T2I models. We create a high-quality dataset... | [
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272828014 | 2409.14205 | 2024-09-21 | Egocentric zone-aware action recognition across environments | Human activities exhibit a strong correlation between actions and the places where these are performed, such as washing something at a sink. More specifically, in daily living environments we may identify particular locations, hereinafter named activity-centric zones, which may afford a set of homogeneous actions. Thei... | [
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272827697 | 2409.14177 | 2024-09-21 | PathSeeker: Exploring LLM Security Vulnerabilities with a Reinforcement Learning-Based Jailbreak Approach | In recent years, Large Language Models (LLMs) have gained widespread use, raising concerns about their security. Traditional jailbreak attacks, which often rely on the model internal information or have limitations when exploring the unsafe behavior of the victim model, limiting their reducing their general applicabili... | [
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272828061 | 2409.14269 | 2024-09-21 | Combining Absolute and Semi-Generalized Relative Poses for Visual Localization | Visual localization is the problem of estimating the camera pose of a given query image within a known scene. Most state-of-the-art localization approaches follow the structure-based paradigm and use 2D-3D matches between pixels in a query image and 3D points in the scene for pose estimation. These approaches assume an... | [
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272826967 | 2409.14106 | 2024-09-21 | Advancing Molecular Graph-Text Pre-training via Fine-grained Alignment | Understanding molecular structure and related knowledge is crucial for scientific research. Recent studies integrate molecular graphs with their textual descriptions to enhance molecular representation learning. However, they focus on the whole molecular graph and neglect frequently occurring subgraphs, known as motifs... | [
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272827488 | 2409.14260 | 2024-09-21 | Perfect Gradient Inversion in Federated Learning: A New Paradigm from the Hidden Subset Sum Problem | Federated Learning (FL) has emerged as a popular paradigm for collaborative learning among multiple parties. It is considered privacy-friendly because local data remains on personal devices, and only intermediate parameters -- such as gradients or model updates -- are shared. Although gradient inversion is widely viewe... | [
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272831861 | 2409.15384 | 2024-09-21 | BurstM: Deep Burst Multi-scale SR using Fourier Space with Optical Flow | Multi frame super-resolution(MFSR) achieves higher performance than single image super-resolution (SISR), because MFSR leverages abundant information from multiple frames. Recent MFSR approaches adapt the deformable convolution network (DCN) to align the frames. However, the existing MFSR suffers from misalignments bet... | [
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272827859 | 2409.14001 | 2024-09-21 | Boolean Product Graph Neural Networks | Graph Neural Networks (GNNs) have recently achieved significant success, with a key operation involving the aggregation of information from neighboring nodes. Substantial researchers have focused on defining neighbors for aggregation, predominantly based on observed adjacency matrices. However, in many scenarios, the e... | [
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272827351 | 2409.13976 | 2024-09-21 | Detecting Inpainted Video with Frequency Domain Insights | Video inpainting enables seamless content removal and replacement within frames, posing ethical and legal risks when misused. To mitigate these risks, detecting manipulated regions in inpainted videos is critical. Previous detection methods often focus solely on the characteristics derived from spatial and temporal dim... | [
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