id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2411.19556 | Differentiable Causal Discovery For Latent Hierarchical Causal Models | [
"cs.LG"
] | Discovering causal structures with latent variables from observational data is a fundamental challenge in causal discovery. Existing methods often rely on constraint-based, iterative discrete searches, limiting their scalability to large numbers of variables. Moreover, these methods frequently assume linearity or inver... | {
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2411.19557 | Initialization using Update Approximation is a Silver Bullet for
Extremely Efficient Low-Rank Fine-Tuning | [
"cs.CL",
"cs.AI",
"cs.LG"
] | Low-rank adapters have become standard for efficiently fine-tuning large language models (LLMs), but they often fall short of achieving the performance of full fine-tuning. We propose a method, LoRA Silver Bullet or LoRA-SB, that approximates full fine-tuning within low-rank subspaces using a carefully designed initial... | {
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2411.19560 | Updating Katz centrality by counting walks | [
"math.NA",
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"cs.SI"
] | We develop efficient and effective strategies for the update of Katz centralities after node and edge removal in simple graphs. We provide explicit formulas for the ``loss of walks" a network suffers when nodes/edges are removed, and use these to inform our algorithms. The theory builds on the newly introduced concept ... | {
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2411.19563 | Ensemble Watermarks for Large Language Models | [
"cs.CL"
] | The rapid advancement of large language models (LLMs) has made it increasingly difficult to distinguish between text written by humans and machines. While watermarks already exist for LLMs, they often lack flexibility, and struggle with attacks such as paraphrasing. To address these issues, we propose a multi-feature m... | {
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2411.19564 | A Comprehensive Framework for Automated Segmentation of Perivascular
Spaces in Brain MRI with the nnU-Net | [
"eess.IV",
"cs.CV",
"cs.LG"
] | Background: Enlargement of perivascular spaces (PVS) is common in neurodegenerative disorders including cerebral small vessel disease, Alzheimer's disease, and Parkinson's disease. PVS enlargement may indicate impaired clearance pathways and there is a need for reliable PVS detection methods which are currently lacking... | {
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2411.19567 | AdvFuzz: Finding More Violations Caused by the EGO Vehicle in Simulation
Testing by Adversarial NPC Vehicles | [
"cs.SE",
"cs.RO"
] | Recently, there has been a significant escalation in both academic and industrial commitment towards the development of autonomous driving systems (ADSs). A number of simulation testing approaches have been proposed to generate diverse driving scenarios for ADS testing. However, scenarios generated by these previous ap... | {
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2411.19568 | Mixed-Integer Linear Programming Model for Collision Avoidance Planning
in Commercial Aircraft Formations | [
"eess.SY",
"cs.SY"
] | With advancements in technology, commercial aircraft formation flying is becoming increasingly feasible as an efficient and environmentally friendly flight method. However, gaps remain in practical implementation, particularly in collision avoidance for aircraft formations. Existing avoidance algorithms mainly focus on... | {
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2411.19571 | Fixed-relative-switch strategies for learning based event-triggered
control of nonlinear multiagent systems | [
"eess.SY",
"cs.SY"
] | This paper investigates event-triggered control for consensus tracking in nonlinear semi-strict-feedback multi-agent systems (MASs) with unknown states and subject to disturbances. We begin by employing radial basis function neural networks combined with the backstepping method to approximate the unknown nonlinear dyna... | {
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2411.19574 | KV Shifting Attention Enhances Language Modeling | [
"cs.CL"
] | The current large language models are mainly based on decode-only structure transformers, which have great in-context learning (ICL) capabilities. It is generally believed that the important foundation of its ICL capability is the induction heads mechanism, which requires at least two layers attention. In order to more... | {
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2411.19576 | On Explaining Recommendations with Large Language Models: A Review | [
"cs.IR",
"cs.HC"
] | The rise of Large Language Models (LLMs), such as LLaMA and ChatGPT, has opened new opportunities for enhancing recommender systems through improved explainability. This paper provides a systematic literature review focused on leveraging LLMs to generate explanations for recommendations -- a critical aspect for fosteri... | {
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2411.19577 | RoadGen: Generating Road Scenarios for Autonomous Vehicle Testing | [
"cs.SE",
"cs.RO"
] | With the rapid development of autonomous vehicles, there is an increasing demand for scenario-based testing to simulate diverse driving scenarios. However, as the base of any driving scenarios, road scenarios (e.g., road topology and geometry) have received little attention by the literature. Despite several advances, ... | {
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2411.19579 | ICPR 2024 Competition on Multilingual Claim-Span Identification | [
"cs.CL"
] | A lot of claims are made in social media posts, which may contain misinformation or fake news. Hence, it is crucial to identify claims as a first step towards claim verification. Given the huge number of social media posts, the task of identifying claims needs to be automated. This competition deals with the task of 'C... | {
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2411.19580 | The ATTUNE model for Artificial Trust Towards Human Operators | [
"cs.RO"
] | This paper presents a novel method to quantify Trust in HRI. It proposes an HRI framework for estimating the Robot Trust towards the Human in the context of a narrow and specified task. The framework produces a real-time estimation of an AI agent's Artificial Trust towards a Human partner interacting with a mobile tele... | {
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2411.19581 | In-Context Learning with Noisy Labels | [
"cs.CL"
] | In-context learning refers to the emerging ability of large language models (LLMs) to perform a target task without additional training, utilizing demonstrations of the task. Recent studies aim to enhance in-context learning performance by selecting more useful demonstrations. However, they overlook the presence of ine... | {
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2411.19582 | Early Versus Late Traffic Management For Autonomous Agents | [
"eess.SY",
"cs.SY"
] | Intersections pose critical challenges in traffic management, where maintaining operational constraints and ensuring safety are essential for efficient flow. This paper investigates the effect of intervention timing in management strategies on maintaining operational constraints at intersections while ensuring safe sep... | {
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2411.19583 | Solving Rubik's Cube Without Tricky Sampling | [
"cs.LG",
"cs.AI"
] | The Rubiks Cube, with its vast state space and sparse reward structure, presents a significant challenge for reinforcement learning (RL) due to the difficulty of reaching rewarded states. Previous research addressed this by propagating cost-to-go estimates from the solved state and incorporating search techniques. Thes... | {
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2411.19584 | Enhancing Sentiment Analysis in Bengali Texts: A Hybrid Approach Using
Lexicon-Based Algorithm and Pretrained Language Model Bangla-BERT | [
"cs.LG"
] | Sentiment analysis (SA) is a process of identifying the emotional tone or polarity within a given text and aims to uncover the user's complex emotions and inner feelings. While sentiment analysis has been extensively studied for languages like English, research in Bengali, remains limited, particularly for fine-grained... | {
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2411.19585 | LDA-AQU: Adaptive Query-guided Upsampling via Local Deformable Attention | [
"cs.CV",
"cs.LG"
] | Feature upsampling is an essential operation in constructing deep convolutional neural networks. However, existing upsamplers either lack specific feature guidance or necessitate the utilization of high-resolution feature maps, resulting in a loss of performance and flexibility. In this paper, we find that the local se... | {
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2411.19588 | Gaussian Splashing: Direct Volumetric Rendering Underwater | [
"cs.CV"
] | In underwater images, most useful features are occluded by water. The extent of the occlusion depends on imaging geometry and can vary even across a sequence of burst images. As a result, 3D reconstruction methods robust on in-air scenes, like Neural Radiance Field methods (NeRFs) or 3D Gaussian Splatting (3DGS), fail ... | {
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2411.19589 | Can Large Language Models Reason about the Region Connection Calculus? | [
"cs.CL"
] | Qualitative Spatial Reasoning is a well explored area of Knowledge Representation and Reasoning and has multiple applications ranging from Geographical Information Systems to Robotics and Computer Vision. Recently, many claims have been made for the reasoning capabilities of Large Language Models (LLMs). Here, we inves... | {
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2411.19593 | Self-Supervised Denoiser Framework | [
"eess.IV",
"cs.CV",
"cs.LG"
] | Reconstructing images using Computed Tomography (CT) in an industrial context leads to specific challenges that differ from those encountered in other areas, such as clinical CT. Indeed, non-destructive testing with industrial CT will often involve scanning multiple similar objects while maintaining high throughput, re... | {
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2411.19594 | Tortho-Gaussian: Splatting True Digital Orthophoto Maps | [
"cs.CV"
] | True Digital Orthophoto Maps (TDOMs) are essential products for digital twins and Geographic Information Systems (GIS). Traditionally, TDOM generation involves a complex set of traditional photogrammetric process, which may deteriorate due to various challenges, including inaccurate Digital Surface Model (DSM), degener... | {
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2411.19598 | Channel Access Strategies for Control-Communication Co-Designed Networks | [
"cs.IT",
"math.IT"
] | We develop a framework for communication-control co-design in a wireless networked control system with multiple geographically separated controllers and controlled systems, modeled via a Poisson point process. Each controlled system consists of an actuator, plant, and sensor. Controllers receive state estimates from se... | {
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2411.19607 | Lyapunov based dynamic controller designs for reach-and-avoid problems | [
"eess.SY",
"cs.SY",
"math.DS",
"math.OC"
] | Safe obstacle avoidance and target set stabilization for nonlinear systems using reactive feedback control is under consideration. Based only on local information and by considering virtual dynamics, a safe path is generated online. The control law for the virtual dynamics is combined with a feedback controller for the... | {
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2411.19617 | Materials Learning Algorithms (MALA): Scalable Machine Learning for
Electronic Structure Calculations in Large-Scale Atomistic Simulations | [
"cond-mat.mtrl-sci",
"cs.LG"
] | We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for large-scale atomistic simulations. Using local descriptors of the atomic environment, MALA models efficiently predict key electronic observa... | {
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2411.19623 | FairDD: Fair Dataset Distillation via Synchronized Matching | [
"cs.CV",
"cs.AI",
"cs.CY",
"cs.LG"
] | Condensing large datasets into smaller synthetic counterparts has demonstrated its promise for image classification. However, previous research has overlooked a crucial concern in image recognition: ensuring that models trained on condensed datasets are unbiased towards protected attributes (PA), such as gender and rac... | {
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2411.19626 | GREAT: Geometry-Intention Collaborative Inference for Open-Vocabulary 3D
Object Affordance Grounding | [
"cs.CV",
"cs.AI"
] | Open-Vocabulary 3D object affordance grounding aims to anticipate ``action possibilities'' regions on 3D objects with arbitrary instructions, which is crucial for robots to generically perceive real scenarios and respond to operational changes. Existing methods focus on combining images or languages that depict interac... | {
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2411.19628 | Accelerating Multimodal Large Language Models via Dynamic Visual-Token
Exit and the Empirical Findings | [
"cs.CV",
"cs.CL",
"cs.LG",
"cs.MM"
] | The excessive use of visual tokens in existing Multimoal Large Language Models (MLLMs) often exhibits obvious redundancy and brings in prohibitively expensive computation. To gain insights into this problem, we first conduct extensive empirical studies on the attention behaviors of MLLMs, and summarize three main infer... | {
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2411.19629 | OpenQDC: Open Quantum Data Commons | [
"physics.chem-ph",
"cs.LG"
] | Machine Learning Interatomic Potentials (MLIPs) are a highly promising alternative to force-fields for molecular dynamics (MD) simulations, offering precise and rapid energy and force calculations. However, Quantum-Mechanical (QM) datasets, crucial for MLIPs, are fragmented across various repositories, hindering access... | {
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2411.19631 | Non-linear Equalization in 112 Gb/s PONs Using Kolmogorov-Arnold
Networks | [
"eess.SP",
"cs.LG"
] | We investigate Kolmogorov-Arnold networks (KANs) for non-linear equalization of 112 Gb/s PAM4 passive optical networks (PONs). Using pruning and extensive hyperparameter search, we outperform linear equalizers and convolutional neural networks at low computational complexity. | {
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2411.19632 | PACMANN: Point Adaptive Collocation Method for Artificial Neural
Networks | [
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"cs.LG",
"cs.NA",
"physics.comp-ph"
] | Physics-Informed Neural Networks (PINNs) are an emerging tool for approximating the solution of Partial Differential Equations (PDEs) in both forward and inverse problems. PINNs minimize a loss function which includes the PDE residual determined for a set of collocation points. Previous work has shown that the number a... | {
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2411.19635 | Build An Influential Bot In Social Media Simulations With Large Language
Models | [
"cs.SI",
"cs.CY"
] | Understanding the dynamics of public opinion evolution on online social platforms is critical for analyzing influence mechanisms. Traditional approaches to influencer analysis are typically divided into qualitative assessments of personal attributes and quantitative evaluations of influence power. In this study, we int... | {
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2411.19638 | LLM Teacher-Student Framework for Text Classification With No Manually
Annotated Data: A Case Study in IPTC News Topic Classification | [
"cs.CL"
] | With the ever-increasing number of news stories available online, classifying them by topic, regardless of the language they are written in, has become crucial for enhancing readers' access to relevant content. To address this challenge, we propose a teacher-student framework based on large language models (LLMs) for d... | {
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2411.19639 | RMIO: A Model-Based MARL Framework for Scenarios with Observation Loss
in Some Agents | [
"cs.MA"
] | In recent years, model-based reinforcement learning (MBRL) has emerged as a solution to address sample complexity in multi-agent reinforcement learning (MARL) by modeling agent-environment dynamics to improve sample efficiency. However, most MBRL methods assume complete and continuous observations from each agent durin... | {
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2411.19640 | Learned Random Label Predictions as a Neural Network Complexity Metric | [
"cs.LG"
] | We empirically investigate the impact of learning randomly generated labels in parallel to class labels in supervised learning on memorization, model complexity, and generalization in deep neural networks. To this end, we introduce a multi-head network architecture as an extension of standard CNN architectures. Inspire... | {
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2411.19647 | CAdam: Confidence-Based Optimization for Online Learning | [
"cs.LG",
"cs.AI",
"stat.ML"
] | Modern recommendation systems frequently employ online learning to dynamically update their models with freshly collected data. The most commonly used optimizer for updating neural networks in these contexts is the Adam optimizer, which integrates momentum ($m_t$) and adaptive learning rate ($v_t$). However, the volati... | {
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2411.19650 | CogACT: A Foundational Vision-Language-Action Model for Synergizing
Cognition and Action in Robotic Manipulation | [
"cs.RO",
"cs.AI",
"cs.CL",
"cs.CV",
"cs.LG"
] | The advancement of large Vision-Language-Action (VLA) models has significantly improved robotic manipulation in terms of language-guided task execution and generalization to unseen scenarios. While existing VLAs adapted from pretrained large Vision-Language-Models (VLM) have demonstrated promising generalizability, the... | {
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2411.19652 | Uniform Attention Maps: Boosting Image Fidelity in Reconstruction and
Editing | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Text-guided image generation and editing using diffusion models have achieved remarkable advancements. Among these, tuning-free methods have gained attention for their ability to perform edits without extensive model adjustments, offering simplicity and efficiency. However, existing tuning-free approaches often struggl... | {
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2411.19653 | Nonparametric Instrumental Regression via Kernel Methods is Minimax
Optimal | [
"stat.ML",
"cs.LG"
] | We study the kernel instrumental variable algorithm of \citet{singh2019kernel}, a nonparametric two-stage least squares (2SLS) procedure which has demonstrated strong empirical performance. We provide a convergence analysis that covers both the identified and unidentified settings: when the structural function cannot b... | {
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2411.19654 | TexGaussian: Generating High-quality PBR Material via Octree-based 3D
Gaussian Splatting | [
"cs.CV",
"cs.GR"
] | Physically Based Rendering (PBR) materials play a crucial role in modern graphics, enabling photorealistic rendering across diverse environment maps. Developing an effective and efficient algorithm that is capable of automatically generating high-quality PBR materials rather than RGB texture for 3D meshes can significa... | {
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2411.19655 | Truth or Mirage? Towards End-to-End Factuality Evaluation with LLM-Oasis | [
"cs.CL"
] | After the introduction of Large Language Models (LLMs), there have been substantial improvements in the performance of Natural Language Generation (NLG) tasks, including Text Summarization and Machine Translation. However, LLMs still produce outputs containing hallucinations, that is, content not grounded in factual in... | {
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2411.19666 | Multimodal Whole Slide Foundation Model for Pathology | [
"eess.IV",
"cs.AI",
"cs.CV",
"cs.LG",
"stat.AP"
] | The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via self-supervised learning (SSL). However, translating these advancements to address complex clinical challe... | {
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2411.19668 | ChineseWebText 2.0: Large-Scale High-quality Chinese Web Text with
Multi-dimensional and fine-grained information | [
"cs.CL",
"cs.AI"
] | During the development of large language models (LLMs), pre-training data play a critical role in shaping LLMs' capabilities. In recent years several large-scale and high-quality pre-training datasets have been released to accelerate the research of LLMs, including ChineseWebText1.0, C4, Pile, WanJuan, MAPCC and others... | {
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} |
2411.19671 | On the Performance Analysis of Momentum Method: A Frequency Domain
Perspective | [
"cs.LG"
] | Momentum-based optimizers are widely adopted for training neural networks. However, the optimal selection of momentum coefficients remains elusive. This uncertainty impedes a clear understanding of the role of momentum in stochastic gradient methods. In this paper, we present a frequency domain analysis framework that ... | {
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2411.19678 | Privacy-Preserving Orthogonal Aggregation for Guaranteeing Gender
Fairness in Federated Recommendation | [
"cs.LG"
] | Under stringent privacy constraints, whether federated recommendation systems can achieve group fairness remains an inadequately explored question. Taking gender fairness as a representative issue, we identify three phenomena in federated recommendation systems: performance difference, data imbalance, and preference di... | {
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2411.19685 | Multiport Network Theory for Modeling and Optimizing Reconfigurable
Metasurfaces | [
"cs.IT",
"eess.SP",
"math.IT"
] | Multiport network theory (MNT) is a powerful analytical tool for modeling and optimizing complex systems based on circuit models. We present an overview of current research on the application of MNT to the development of electromagnetically consistent models for programmable metasurfaces, with focus on reconfigurable i... | {
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2411.19687 | State of the Art on Stacked Intelligent Metasurfaces: Communication,
Sensing and Computing in the Wave Domain | [
"cs.IT",
"eess.SP",
"math.IT"
] | Stacked intelligent metasurface (SIM) is an emerging technology that capitalizes on reconfigurable metasurfaces for several applications in wireless communications. SIM is considered an enabler for integrating communication, sensing and computing in a unique platform. In this paper, we offer a survey on the state of th... | {
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2411.19688 | SURE-VQA: Systematic Understanding of Robustness Evaluation in Medical
VQA Tasks | [
"cs.CV",
"cs.LG"
] | Vision-Language Models (VLMs) have great potential in medical tasks, like Visual Question Answering (VQA), where they could act as interactive assistants for both patients and clinicians. Yet their robustness to distribution shifts on unseen data remains a critical concern for safe deployment. Evaluating such robustnes... | {
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2411.19689 | MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating
Multi-Insight Multi-Document Extraction Tasks | [
"cs.CL"
] | Large language models (LLMs) have demonstrated remarkable capabilities in text analysis tasks, yet their evaluation on complex, real-world applications remains challenging. We define a set of tasks, Multi-Insight Multi-Document Extraction (MIMDE) tasks, which involves extracting an optimal set of insights from a docume... | {
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2411.19690 | Gated-Attention Feature-Fusion Based Framework for Poverty Prediction | [
"cs.CV",
"cs.CY",
"cs.LG"
] | This research paper addresses the significant challenge of accurately estimating poverty levels using deep learning, particularly in developing regions where traditional methods like household surveys are often costly, infrequent, and quickly become outdated. To address these issues, we propose a state-of-the-art Convo... | {
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2411.19700 | Explaining the Impact of Training on Vision Models via Activation
Clustering | [
"cs.CV",
"cs.LG"
] | Recent developments in the field of explainable artificial intelligence (XAI) for vision models investigate the information extracted by their feature encoder. We contribute to this effort and propose Neuro-Activated Vision Explanations (NAVE), which extracts the information captured by the encoder by clustering the fe... | {
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2411.19702 | Fast Mutual Information Computation for Large Binary Datasets | [
"cs.LG",
"cs.IT",
"cs.NA",
"math.IT",
"math.NA"
] | Mutual Information (MI) is a powerful statistical measure that quantifies shared information between random variables, particularly valuable in high-dimensional data analysis across fields like genomics, natural language processing, and network science. However, computing MI becomes computationally prohibitive for larg... | {
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2411.19710 | Know Your RAG: Dataset Taxonomy and Generation Strategies for Evaluating
RAG Systems | [
"cs.IR",
"cs.LG"
] | Retrieval Augmented Generation (RAG) systems are a widespread application of Large Language Models (LLMs) in the industry. While many tools exist empowering developers to build their own systems, measuring their performance locally, with datasets reflective of the system's use cases, is a technological challenge. Solut... | {
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2411.19713 | CantorNet: A Sandbox for Testing Geometrical and Topological Complexity
Measures | [
"cs.NE",
"cs.AI",
"stat.ML"
] | Many natural phenomena are characterized by self-similarity, for example the symmetry of human faces, or a repetitive motif of a song. Studying of such symmetries will allow us to gain deeper insights into the underlying mechanisms of complex systems. Recognizing the importance of understanding these patterns, we propo... | {
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2411.19714 | The Streetscape Application Services Stack (SASS): Towards a Distributed
Sensing Architecture for Urban Applications | [
"cs.NI",
"cs.CV",
"cs.DC",
"cs.LG"
] | As urban populations grow, cities are becoming more complex, driving the deployment of interconnected sensing systems to realize the vision of smart cities. These systems aim to improve safety, mobility, and quality of life through applications that integrate diverse sensors with real-time decision-making. Streetscape ... | {
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2411.19715 | Forensics Adapter: Adapting CLIP for Generalizable Face Forgery
Detection | [
"cs.CV",
"cs.CR",
"cs.LG"
] | We describe the Forensics Adapter, an adapter network designed to transform CLIP into an effective and generalizable face forgery detector. Although CLIP is highly versatile, adapting it for face forgery detection is non-trivial as forgery-related knowledge is entangled with a wide range of unrelated knowledge. Existin... | {
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2411.19717 | MonoPP: Metric-Scaled Self-Supervised Monocular Depth Estimation by
Planar-Parallax Geometry in Automotive Applications | [
"cs.CV",
"cs.AI",
"cs.LG",
"cs.RO"
] | Self-supervised monocular depth estimation (MDE) has gained popularity for obtaining depth predictions directly from videos. However, these methods often produce scale invariant results, unless additional training signals are provided. Addressing this challenge, we introduce a novel self-supervised metric-scaled MDE mo... | {
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2411.19718 | TakeLab Retriever: AI-Driven Search Engine for Articles from Croatian
News Outlets | [
"cs.CL",
"cs.IR"
] | TakeLab Retriever is an AI-driven search engine designed to discover, collect, and semantically analyze news articles from Croatian news outlets. It offers a unique perspective on the history and current landscape of Croatian online news media, making it an essential tool for researchers seeking to uncover trends, patt... | {
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} |
2411.19719 | Relative Representations of Latent Spaces enable Efficient Semantic
Channel Equalization | [
"cs.LG"
] | In multi-user semantic communication, language mismatche poses a significant challenge when independently trained agents interact. We present a novel semantic equalization algorithm that enables communication between agents with different languages without additional retraining. Our algorithm is based on relative repre... | {
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2411.19722 | JetFormer: An Autoregressive Generative Model of Raw Images and Text | [
"cs.LG",
"cs.AI",
"cs.CV"
] | Removing modeling constraints and unifying architectures across domains has been a key driver of the recent progress in training large multimodal models. However, most of these models still rely on many separately trained components such as modality-specific encoders and decoders. In this work, we further streamline jo... | {
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2411.19726 | Towards Santali Linguistic Inclusion: Building the First
Santali-to-English Translation Model using mT5 Transformer and Data
Augmentation | [
"cs.CL",
"cs.LG"
] | Around seven million individuals in India, Bangladesh, Bhutan, and Nepal speak Santali, positioning it as nearly the third most commonly used Austroasiatic language. Despite its prominence among the Austroasiatic language family's Munda subfamily, Santali lacks global recognition. Currently, no translation models exist... | {
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2411.19729 | Risk-Averse Certification of Bayesian Neural Networks | [
"cs.LG"
] | In light of the inherently complex and dynamic nature of real-world environments, incorporating risk measures is crucial for the robustness evaluation of deep learning models. In this work, we propose a Risk-Averse Certification framework for Bayesian neural networks called RAC-BNN. Our method leverages sampling and op... | {
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2411.19731 | Real-Time Anomaly Detection in Video Streams | [
"cs.CV",
"cs.LG"
] | This thesis is part of a CIFRE agreement between the company Othello and the LIASD laboratory. The objective is to develop an artificial intelligence system that can detect real-time dangers in a video stream. To achieve this, a novel approach combining temporal and spatial analysis has been proposed. Several avenues h... | {
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2411.19732 | Improving generalization of robot locomotion policies via
Sharpness-Aware Reinforcement Learning | [
"cs.RO",
"cs.AI",
"cs.LG"
] | Reinforcement learning often requires extensive training data. Simulation-to-real transfer offers a promising approach to address this challenge in robotics. While differentiable simulators offer improved sample efficiency through exact gradients, they can be unstable in contact-rich environments and may lead to poor g... | {
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2411.19733 | A Deep Learning Approach to Language-independent Gender Prediction on
Twitter | [
"cs.CL"
] | This work presents a set of experiments conducted to predict the gender of Twitter users based on language-independent features extracted from the text of the users' tweets. The experiments were performed on a version of TwiSty dataset including tweets written by the users of six different languages: Portuguese, French... | {
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2411.19734 | A Note on Small Percolating Sets on Hypercubes via Generative AI | [
"cs.LG",
"cs.DM"
] | We apply a generative AI pattern-recognition technique called PatternBoost to study bootstrap percolation on hypercubes. With this, we slightly improve the best existing upper bound for the size of percolating subsets of the hypercube. | {
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2411.19742 | Graph Neural Networks for Heart Failure Prediction on an EHR-Based
Patient Similarity Graph | [
"cs.LG",
"cs.AI"
] | Objective: In modern healthcare, accurately predicting diseases is a crucial matter. This study introduces a novel approach using graph neural networks (GNNs) and a Graph Transformer (GT) to predict the incidence of heart failure (HF) on a patient similarity graph at the next hospital visit. Materials and Methods: We u... | {
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2411.19744 | Amplifying human performance in combinatorial competitive programming | [
"cs.LG",
"cs.AI",
"cs.NE",
"cs.PL"
] | Recent years have seen a significant surge in complex AI systems for competitive programming, capable of performing at admirable levels against human competitors. While steady progress has been made, the highest percentiles still remain out of reach for these methods on standard competition platforms such as Codeforces... | {
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2411.19746 | HVAC-DPT: A Decision Pretrained Transformer for HVAC Control | [
"cs.LG",
"cs.AI",
"cs.MA"
] | Building operations consume approximately 40% of global energy, with Heating, Ventilation, and Air Conditioning (HVAC) systems responsible for up to 50% of this consumption. As HVAC energy demands are expected to rise, optimising system efficiency is crucial for reducing future energy use and mitigating climate change.... | {
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2411.19747 | A Multi-Loss Strategy for Vehicle Trajectory Prediction: Combining
Off-Road, Diversity, and Directional Consistency Losses | [
"cs.CV",
"cs.AI",
"cs.LG",
"cs.MA",
"cs.RO"
] | Trajectory prediction is essential for the safety and efficiency of planning in autonomous vehicles. However, current models often fail to fully capture complex traffic rules and the complete range of potential vehicle movements. Addressing these limitations, this study introduces three novel loss functions: Offroad Lo... | {
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2411.19750 | A Comprehensive Content Verification System for ensuring Digital
Integrity in the Age of Deep Fakes | [
"cs.CR",
"cs.CV",
"cs.ET"
] | In an era marked by the widespread sharing of digital content, the need for a robust content-integrity verification goes beyond the confines of individual social media platforms. While verified profiles (such as blue ticks on platforms like Instagram and X) have become synonymous with credibility, the content they shar... | {
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2411.19753 | URDF+: An Enhanced URDF for Robots with Kinematic Loops | [
"cs.RO"
] | Designs incorporating kinematic loops are becoming increasingly prevalent in the robotics community. Despite the existence of dynamics algorithms to deal with the effects of such loops, many modern simulators rely on dynamics libraries that require robots to be represented as kinematic trees. This requirement is reflec... | {
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2411.19754 | Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of
Wireless Communications | [
"cs.IT",
"eess.SP",
"math.IT"
] | Intelligent metasurfaces have demonstrated great promise in revolutionizing wireless communications. One notable example is the two-dimensional (2D) programmable metasurface, which is also known as reconfigurable intelligent surfaces (RIS) to manipulate the wireless propagation environment to enhance network coverage. ... | {
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2411.19756 | DeSplat: Decomposed Gaussian Splatting for Distractor-Free Rendering | [
"cs.CV",
"cs.LG"
] | Gaussian splatting enables fast novel view synthesis in static 3D environments. However, reconstructing real-world environments remains challenging as distractors or occluders break the multi-view consistency assumption required for accurate 3D reconstruction. Most existing methods rely on external semantic information... | {
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2411.19757 | Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning
Zero-Shot Models | [
"cs.LG",
"cs.CV"
] | Fine-tuning foundation models often compromises their robustness to distribution shifts. To remedy this, most robust fine-tuning methods aim to preserve the pre-trained features. However, not all pre-trained features are robust and those methods are largely indifferent to which ones to preserve. We propose dual risk mi... | {
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2411.19758 | LaVIDE: A Language-Vision Discriminator for Detecting Changes in
Satellite Image with Map References | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Change detection, which typically relies on the comparison of bi-temporal images, is significantly hindered when only a single image is available. Comparing a single image with an existing map, such as OpenStreetMap, which is continuously updated through crowd-sourcing, offers a viable solution to this challenge. Unlik... | {
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2411.19763 | Forecasting Foreign Exchange Market Prices Using Technical Indicators
with Deep Learning and Attention Mechanism | [
"cs.LG",
"cs.AI"
] | Accurate prediction of price behavior in the foreign exchange market is crucial. This paper proposes a novel approach that leverages technical indicators and deep neural networks. The proposed architecture consists of a Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN), and attention mechanism. Initi... | {
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2411.19765 | Secure Filtering against Spatio-Temporal False Data under Asynchronous
Sampling | [
"eess.SY",
"cs.SY"
] | This paper addresses the state estimation problem in continuous LTI systems under attacks with non-periodic and asynchronous sampled measurements. The non-periodic and asynchronous sampling requires sensors to transmit not only the measurement values but also the sampling time-stamps to the fusion center via unprotecte... | {
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2411.19766 | Stock Price Prediction using Multi-Faceted Information based on Deep
Recurrent Neural Networks | [
"cs.LG",
"cs.AI"
] | Accurate prediction of stock market trends is crucial for informed investment decisions and effective portfolio management, ultimately leading to enhanced wealth creation and risk mitigation. This study proposes a novel approach for predicting stock prices in the stock market by integrating Convolutional Neural Network... | {
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2411.19769 | Riemannian Denoising Score Matching for Molecular Structure Optimization
with Accurate Energy | [
"cs.LG",
"physics.chem-ph"
] | This study introduces a modified score matching method aimed at generating molecular structures with high energy accuracy. The denoising process of score matching or diffusion models mirrors molecular structure optimization, where scores act like physical force fields that guide particles toward equilibrium states. To ... | {
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2411.19770 | Noro: A Noise-Robust One-shot Voice Conversion System with Hidden
Speaker Representation Capabilities | [
"cs.SD",
"cs.CL",
"eess.AS"
] | One-shot voice conversion (VC) aims to alter the timbre of speech from a source speaker to match that of a target speaker using just a single reference speech from the target, while preserving the semantic content of the original source speech. Despite advancements in one-shot VC, its effectiveness decreases in real-wo... | {
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2411.19772 | LongVALE: Vision-Audio-Language-Event Benchmark Towards Time-Aware
Omni-Modal Perception of Long Videos | [
"cs.CV",
"cs.CL",
"cs.LG",
"cs.MM"
] | Despite impressive advancements in video understanding, most efforts remain limited to coarse-grained or visual-only video tasks. However, real-world videos encompass omni-modal information (vision, audio, and speech) with a series of events forming a cohesive storyline. The lack of multi-modal video data with fine-gra... | {
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2411.19774 | PerLA: Perceptive 3D Language Assistant | [
"cs.CV",
"cs.CL",
"cs.LG"
] | Enabling Large Language Models (LLMs) to understand the 3D physical world is an emerging yet challenging research direction. Current strategies for processing point clouds typically downsample the scene or divide it into smaller parts for separate analysis. However, both approaches risk losing key local details or glob... | {
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2411.19780 | Machine learning force-field model for kinetic Monte Carlo simulations
of itinerant Ising magnets | [
"cond-mat.stat-mech",
"cond-mat.str-el",
"cs.LG"
] | We present a scalable machine learning (ML) framework for large-scale kinetic Monte Carlo (kMC) simulations of itinerant electron Ising systems. As the effective interactions between Ising spins in such itinerant magnets are mediated by conducting electrons, the calculation of energy change due to a local spin update r... | {
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2411.19786 | MoTe: Learning Motion-Text Diffusion Model for Multiple Generation Tasks | [
"cs.CV",
"cs.CL",
"cs.LG"
] | Recently, human motion analysis has experienced great improvement due to inspiring generative models such as the denoising diffusion model and large language model. While the existing approaches mainly focus on generating motions with textual descriptions and overlook the reciprocal task. In this paper, we present~\tex... | {
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2411.19787 | CAREL: Instruction-guided reinforcement learning with cross-modal
auxiliary objectives | [
"cs.LG",
"cs.AI"
] | Grounding the instruction in the environment is a key step in solving language-guided goal-reaching reinforcement learning problems. In automated reinforcement learning, a key concern is to enhance the model's ability to generalize across various tasks and environments. In goal-reaching scenarios, the agent must compre... | {
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2411.19791 | Tractable Agreement Protocols | [
"cs.LG",
"cs.DS",
"cs.GT"
] | We present an efficient reduction that converts any machine learning algorithm into an interactive protocol, enabling collaboration with another party (e.g., a human) to achieve consensus on predictions and improve accuracy. This approach imposes calibration conditions on each party, which are computationally and stati... | {
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2411.19793 | Voice Communication Analysis in Esports | [
"cs.SD",
"cs.AI",
"cs.CL",
"eess.AS"
] | In most team-based esports, voice communications are prominent in the team efficiency and synergy. In fact it has been observed that not only the skill aspect of the team but also the team effective voice communication comes into play when trying to have good performance in official matches. With the recent emergence o... | {
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2411.19795 | Characterization of Spatial-Temporal Channel Statistics from Measurement
Data at D Band | [
"cs.IT",
"eess.SP",
"math.IT"
] | Millimeter-Wave (mmWave) (30-300 GHz) and D band (110-170 GHz) frequencies are poised to play a pivotal role in the advancement of sixth-generation (6G) systems and beyond with increased demand for greater bandwidth and capacity. This paper focuses on deriving a generalized channel impulse response for mmWave communica... | {
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2411.19798 | Rethinking the initialization of Momentum in Federated Learning with
Heterogeneous Data | [
"cs.LG"
] | Data Heterogeneity is a major challenge of Federated Learning performance. Recently, momentum based optimization techniques have beed proved to be effective in mitigating the heterogeneity issue. Along with the model updates, the momentum updates are transmitted to the server side and aggregated. Therefore, the local t... | {
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} |
2411.19799 | INCLUDE: Evaluating Multilingual Language Understanding with Regional
Knowledge | [
"cs.CL"
] | The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal value of generative AI tools in many communities. However, the development of functional LLMs in many languages (\ie, multilingual LLMs) is bot... | {
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} |
2411.19803 | A Cross-Corpus Speech Emotion Recognition Method Based on Supervised
Contrastive Learning | [
"cs.SD",
"cs.CL",
"eess.AS"
] | Research on Speech Emotion Recognition (SER) often faces challenges such as the lack of large-scale public datasets and limited generalization capability when dealing with data from different distributions. To solve this problem, this paper proposes a cross-corpus speech emotion recognition method based on supervised c... | {
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} |
2411.19804 | Advanced System Integration: Analyzing OpenAPI Chunking for
Retrieval-Augmented Generation | [
"cs.SE",
"cs.AI"
] | Integrating multiple (sub-)systems is essential to create advanced Information Systems (ISs). Difficulties mainly arise when integrating dynamic environments across the IS lifecycle. A traditional approach is a registry that provides the API documentation of the systems' endpoints. Large Language Models (LLMs) have sho... | {
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} |
2411.19806 | Zero-shot Musical Stem Retrieval with Joint-Embedding Predictive
Architectures | [
"cs.SD",
"cs.AI",
"eess.AS"
] | In this paper, we tackle the task of musical stem retrieval. Given a musical mix, it consists in retrieving a stem that would fit with it, i.e., that would sound pleasant if played together. To do so, we introduce a new method based on Joint-Embedding Predictive Architectures, where an encoder and a predictor are joint... | {
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"cs.SD": 1,
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} |
2411.19809 | Q-learning-based Model-free Safety Filter | [
"cs.RO",
"cs.AI",
"cs.SY",
"eess.SY"
] | Ensuring safety via safety filters in real-world robotics presents significant challenges, particularly when the system dynamics is complex or unavailable. To handle this issue, learning-based safety filters recently gained popularity, which can be classified as model-based and model-free methods. Existing model-based ... | {
"Other": 0,
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"cs.SY": 1
} |
2411.19814 | Gaussian multi-target filtering with target dynamics driven by a
stochastic differential equation | [
"cs.CV",
"eess.SP",
"math.PR",
"stat.CO"
] | This paper proposes multi-target filtering algorithms in which target dynamics are given in continuous time and measurements are obtained at discrete time instants. In particular, targets appear according to a Poisson point process (PPP) in time with a given Gaussian spatial distribution, targets move according to a ge... | {
"Other": 0,
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"cs.SD": 0,
"cs.SI": 0,
"cs.SY": 0
} |
2411.19819 | GradAlign for Training-free Model Performance Inference | [
"cs.LG"
] | Architecture plays an important role in deciding the performance of deep neural networks. However, the search for the optimal architecture is often hindered by the vast search space, making it a time-intensive process. Recently, a novel approach known as training-free neural architecture search (NAS) has emerged, aimin... | {
"Other": 0,
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"cs.SD": 0,
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"cs.SY": 0
} |
2411.19820 | Integrated Artificial Neurons from Metal Halide Perovskites | [
"cond-mat.mtrl-sci",
"cs.ET",
"cs.NE"
] | Hardware neural networks could perform certain computational tasks orders of magnitude more energy-efficiently than conventional computers. Artificial neurons are a key component of these networks and are currently implemented with electronic circuits based on capacitors and transistors. However, artificial neurons bas... | {
"Other": 1,
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"cs.SY": 0
} |
2411.19822 | SDR-GNN: Spectral Domain Reconstruction Graph Neural Network for
Incomplete Multimodal Learning in Conversational Emotion Recognition | [
"cs.CL"
] | Multimodal Emotion Recognition in Conversations (MERC) aims to classify utterance emotions using textual, auditory, and visual modal features. Most existing MERC methods assume each utterance has complete modalities, overlooking the common issue of incomplete modalities in real-world scenarios. Recently, graph neural n... | {
"Other": 0,
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"cs.NE": 0,
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"cs.SD": 0,
"cs.SI": 0,
"cs.SY": 0
} |
2411.19824 | SAT-HMR: Real-Time Multi-Person 3D Mesh Estimation via Scale-Adaptive
Tokens | [
"cs.CV"
] | We propose a one-stage framework for real-time multi-person 3D human mesh estimation from a single RGB image. While current one-stage methods, which follow a DETR-style pipeline, achieve state-of-the-art (SOTA) performance with high-resolution inputs, we observe that this particularly benefits the estimation of individ... | {
"Other": 0,
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"cs.SI": 0,
"cs.SY": 0
} |
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