id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.20651 | Latent Drifting in Diffusion Models for Counterfactual Medical Image
Synthesis | [
"cs.CV",
"cs.AI"
] | Scaling by training on large datasets has been shown to enhance the quality and fidelity of image generation and manipulation with diffusion models; however, such large datasets are not always accessible in medical imaging due to cost and privacy issues, which contradicts one of the main applications of such models to ... | {
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2412.20654 | Impact of Cognitive Load on Human Trust in Hybrid Human-Robot
Collaboration | [
"cs.RO",
"cs.HC"
] | Human trust plays a crucial role in the effectiveness of human-robot collaboration. Despite its significance, the development and maintenance of an optimal trust level are obstructed by the complex nature of influencing factors and their mechanisms. This study investigates the effects of cognitive load on human trust w... | {
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2412.20656 | Overcoming Class Imbalance: Unified GNN Learning with Structural and
Semantic Connectivity Representations | [
"cs.LG",
"cs.AI"
] | Class imbalance is pervasive in real-world graph datasets, where the majority of annotated nodes belong to a small set of classes (majority classes), leaving many other classes (minority classes) with only a handful of labeled nodes. Graph Neural Networks (GNNs) suffer from significant performance degradation in the pr... | {
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2412.20657 | Diffgrasp: Whole-Body Grasping Synthesis Guided by Object Motion Using a
Diffusion Model | [
"cs.CV"
] | Generating high-quality whole-body human object interaction motion sequences is becoming increasingly important in various fields such as animation, VR/AR, and robotics. The main challenge of this task lies in determining the level of involvement of each hand given the complex shapes of objects in different sizes and t... | {
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2412.20659 | Nanosatellite Design Considerations for a Mission to Explore the
Propellant Sloshing Problem | [
"eess.SY",
"cs.SY"
] | Sloshing Platform for In-Orbit Controller Experimentation is an ambitious, student run mission to design and fly a cubesat to study fluid sloshing in spacecraft. The project will examine zero-g propellant sloshing from an experimental standpoint. Despite the small size and limited payload capacity, we intend to use the... | {
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2412.20662 | Enhancing Table Recognition with Vision LLMs: A Benchmark and
Neighbor-Guided Toolchain Reasoner | [
"cs.CV",
"cs.AI"
] | Pre-trained foundation models have recently significantly progressed in structured table understanding and reasoning. However, despite advancements in areas such as table semantic understanding and table question answering, recognizing the structure and content of unstructured tables using Vision Large Language Models ... | {
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2412.20665 | SM3Det: A Unified Model for Multi-Modal Remote Sensing Object Detection | [
"cs.CV",
"cs.MM"
] | With the rapid advancement of remote sensing technology, high-resolution multi-modal imagery is now more widely accessible. Conventional Object detection models are trained on a single dataset, often restricted to a specific imaging modality and annotation format. However, such an approach overlooks the valuable shared... | {
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2412.20666 | Recurrence-based Vanishing Point Detection | [
"cs.CV"
] | Classical approaches to Vanishing Point Detection (VPD) rely solely on the presence of explicit straight lines in images, while recent supervised deep learning approaches need labeled datasets for training. We propose an alternative unsupervised approach: Recurrence-based Vanishing Point Detection (R-VPD) that uses imp... | {
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2412.20667 | Highway Managed Lane Usage and Tolling for Mixed Traffic Flows with
Connected Automated Vehicles (CAVs) and High-Occupancy Vehicles (HOVs) | [
"eess.SY",
"cs.SY",
"math.OC"
] | This paper investigates managed lane (ML) toll setting and its effect under mixed traffic of connected automated vehicles (CAVs), high-occupancy vehicles (HOVs), and human-driven vehicles (HDVs), with a goal to avoid flow breakdown and minimize total social cost. A mesoscopic finite-difference traffic simulation model ... | {
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2412.20670 | Prototypical Distillation and Debiased Tuning for Black-box Unsupervised
Domain Adaptation | [
"cs.LG",
"cs.CV"
] | Unsupervised domain adaptation aims to transfer knowledge from a related, label-rich source domain to an unlabeled target domain, thereby circumventing the high costs associated with manual annotation. Recently, there has been growing interest in source-free domain adaptation, a paradigm in which only a pre-trained mod... | {
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2412.20671 | Two Birds with One Stone: Improving Rumor Detection by Addressing the
Unfairness Issue | [
"cs.SI",
"cs.LG"
] | The degraded performance and group unfairness caused by confounding sensitive attributes in rumor detection remains relatively unexplored. To address this, we propose a two-step framework. Initially, it identifies confounding sensitive attributes that limit rumor detection performance and cause unfairness across groups... | {
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2412.20674 | Blockchain-Empowered Cyber-Secure Federated Learning for Trustworthy
Edge Computing | [
"cs.DC",
"cs.CR",
"cs.LG"
] | Federated Learning (FL) is a privacy-preserving distributed machine learning scheme, where each participant data remains on the participating devices and only the local model generated utilizing the local computational power is transmitted throughout the database. However, the distributed computational nature of FL cre... | {
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2412.20675 | Improved ICNN-LSTM Model Classification Based on Attitude Sensor Data
for Hazardous State Assessment of Magnetic Adhesion Climbing Wall Robots | [
"cs.RO",
"eess.SP",
"physics.ins-det"
] | Magnetic adhesion tracked climbing robots are widely utilized in high-altitude inspection, welding, and cleaning tasks due to their ability to perform various operations against gravity on vertical or inclined walls. However, during operation, the robot may experience overturning torque caused by its own weight and loa... | {
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2412.20677 | Align Attention Heads Before Merging Them: An Effective Way for
Converting MHA to GQA | [
"cs.CL"
] | Large language models have been shown to perform well on a variety of natural language processing problems. However, as the model size and the input sequence's length increase, the rapid increase of KV Cache significantly slows down inference speed. Therefore GQA model, as an alternative to MHA model, has been widely i... | {
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2412.20678 | Attention-Driven Metapath Encoding in Heterogeneous Graphs | [
"cs.LG"
] | One of the emerging techniques in node classification in heterogeneous graphs is to restrict message aggregation to pre-defined, semantically meaningful structures called metapaths. This work is the first attempt to incorporate attention into the process of encoding entire metapaths without dropping intermediate nodes.... | {
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2412.20679 | Differentiable Convex Optimization Layers in Neural Architectures:
Foundations and Perspectives | [
"cs.LG",
"math.OC"
] | The integration of optimization problems within neural network architectures represents a fundamental shift from traditional approaches to handling constraints in deep learning. While it is long known that neural networks can incorporate soft constraints with techniques such as regularization, strict adherence to hard ... | {
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2412.20680 | Online Adaptive Platoon Control for Connected and Automated Vehicles via
Physics Enhanced Residual Learning | [
"cs.RO",
"cs.SY",
"eess.SY"
] | This paper introduces a physics enhanced residual learning (PERL) framework for connected and automated vehicle (CAV) platoon control, addressing the dynamics and unpredictability inherent to platoon systems. The framework first develops a physics-based controller to model vehicle dynamics, using driving speed as input... | {
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2412.20682 | Learning to Rank Pre-trained Vision-Language Models for Downstream Tasks | [
"cs.CV",
"cs.LG"
] | Vision language models (VLMs) like CLIP show stellar zero-shot capability on classification benchmarks. However, selecting the VLM with the highest performance on the unlabeled downstream task is non-trivial. Existing VLM selection methods focus on the class-name-only setting, relying on a supervised large-scale datase... | {
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2412.20687 | Powering the Future: Innovations in Electric Vehicle Battery Recycling | [
"cs.CE"
] | The global shift towards electric vehicles (EVs) as a sustainable alternative to traditional gasoline-powered cars has triggered a significant rise in the demand for lithium-ion batteries. However, as the adoption of EVs grows, the issue of battery disposal and recycling has emerged as a critical challenge. The recycli... | {
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2412.20688 | Revolutionizing Mobility:The Latest Advancements in Autonomous Vehicle
Technology | [
"cs.CE"
] | Autonomous vehicle (AV) technology is transforming the landscape of transportation bypromising safer, more efficient, and sustainable mobilitysolutions. In recent years, significant advancements in AI, machine learning, sensor fusion, and vehicle-to-everything(V2X)communicationhavepropelledthedevelopmentoffullyautonomo... | {
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2412.20694 | QUBE: Enhancing Automatic Heuristic Design via Quality-Uncertainty
Balanced Evolution | [
"cs.NE",
"cs.AI",
"cs.CL"
] | Solving NP-hard problems traditionally relies on heuristics, yet manually designing effective heuristics for complex problems remains a significant challenge. While recent advancements like FunSearch have shown that large language models (LLMs) can be integrated into evolutionary algorithms (EAs) for heuristic design, ... | {
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2412.20695 | CoCap: Coordinated motion Capture for multi-actor scenes in outdoor
environments | [
"cs.RO"
] | Motion capture has become increasingly important, not only in computer animation but also in emerging fields like the virtual reality, bioinformatics, and humanoid training. Capturing outdoor environments offers extended horizon scenes but introduces challenges with occlusions and obstacles. Recent approaches using mul... | {
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2412.20699 | Air-Ground Collaborative Robots for Fire and Rescue Missions: Towards
Mapping and Navigation Perspective | [
"cs.RO"
] | Air-ground collaborative robots have shown great potential in the field of fire and rescue, which can quickly respond to rescue needs and improve the efficiency of task execution. Mapping and navigation, as the key foundation for air-ground collaborative robots to achieve efficient task execution, have attracted a grea... | {
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2412.20701 | Open-Set Object Detection By Aligning Known Class Representations | [
"cs.CV"
] | Open-Set Object Detection (OSOD) has emerged as a contemporary research direction to address the detection of unknown objects. Recently, few works have achieved remarkable performance in the OSOD task by employing contrastive clustering to separate unknown classes. In contrast, we propose a new semantic clustering-base... | {
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2412.20704 | HFI: A unified framework for training-free detection and implicit
watermarking of latent diffusion model generated images | [
"cs.CV",
"cs.LG"
] | Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-generated image detection methods assume the availability of real/AI-generated images for training, this is practically limited given the vast expressibility of LDMs. This motiva... | {
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2412.20709 | Residual Connection Networks in Medical Image Processing: Exploration of
ResUnet++ Model Driven by Human Computer Interaction | [
"eess.IV",
"cs.CV"
] | Accurate identification and localisation of brain tumours from medical images remain challenging due to tumour variability and structural complexity. Convolutional Neural Networks (CNNs), particularly ResNet and Unet, have made significant progress in medical image processing, offering robust capabilities for image seg... | {
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2412.20715 | ChartAdapter: Large Vision-Language Model for Chart Summarization | [
"cs.MM",
"cs.CL"
] | Chart summarization, which focuses on extracting key information from charts and interpreting it in natural language, is crucial for generating and delivering insights through effective and accessible data analysis. Traditional methods for chart understanding and summarization often rely on multi-stage pipelines, which... | {
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2412.20717 | Closing Speed Computation using Stereo Camera and Applications in
Unsignalized T-Intersection | [
"cs.RO"
] | This letter presents a conflict resolution strategy for an autonomous vehicle mounted with a stereo camera approaching an unsignalized T-intersection. A mathematical model for uncertainty in stereo camera depth measurements is considered and an analysis establishes the proposed adaptive depth sampling logic which guara... | {
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2412.20718 | M$^3$oralBench: A MultiModal Moral Benchmark for LVLMs | [
"cs.CV",
"cs.AI"
] | Recently, large foundation models, including large language models (LLMs) and large vision-language models (LVLMs), have become essential tools in critical fields such as law, finance, and healthcare. As these models increasingly integrate into our daily life, it is necessary to conduct moral evaluation to ensure that ... | {
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2412.20720 | 4D Gaussian Splatting: Modeling Dynamic Scenes with Native 4D Primitives | [
"cs.CV"
] | Dynamic 3D scene representation and novel view synthesis from captured videos are crucial for enabling immersive experiences required by AR/VR and metaverse applications. However, this task is challenging due to the complexity of unconstrained real-world scenes and their temporal dynamics. In this paper, we frame dynam... | {
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2412.20724 | Training Deep Neural Classifiers with Soft Diamond Regularizers | [
"stat.ML",
"cs.LG"
] | We introduce new \emph{soft diamond} regularizers that both improve synaptic sparsity and maintain classification accuracy in deep neural networks. These parametrized regularizers outperform the state-of-the-art hard-diamond Laplacian regularizer of Lasso regression and classification. They use thick-tailed symmetric a... | {
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2412.20725 | Dialogue Director: Bridging the Gap in Dialogue Visualization for
Multimodal Storytelling | [
"cs.CV"
] | Recent advances in AI-driven storytelling have enhanced video generation and story visualization. However, translating dialogue-centric scripts into coherent storyboards remains a significant challenge due to limited script detail, inadequate physical context understanding, and the complexity of integrating cinematic p... | {
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2412.20726 | Beam Codebook Refinement for mmWave Devices with Random Orientations:
Concept and Experimental Validation | [
"cs.IT",
"eess.SP",
"math.IT"
] | There is a growing interest in codebook-based beam-steering for millimeter-wave (mmWave) systems due to its potential for low complexity and rapid beam search. A key focus of recent research has been the design of codebooks that strike a trade-off between achievable gain and codebook size, which directly impacts beam s... | {
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2412.20727 | AverageLinear: Enhance Long-Term Time series forcasting with simple
averaging | [
"cs.LG",
"stat.ML"
] | Long-term time series analysis aims to forecast long-term trends by examining changes over past and future periods. The intricacy of time series data poses significant challenges for modeling. Models based on the Transformer architecture, through the application of attention mechanisms to channels and sequences, have d... | {
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2412.20732 | Joint Scoring Rules: Zero-Sum Competition Avoids Performative Prediction | [
"cs.LG"
] | In a decision-making scenario, a principal could use conditional predictions from an expert agent to inform their choice. However, this approach would introduce a fundamental conflict of interest. An agent optimizing for predictive accuracy is incentivized to manipulate their principal towards more predictable actions,... | {
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2412.20733 | Towards nation-wide analytical healthcare infrastructures: A
privacy-preserving augmented knee rehabilitation case study | [
"cs.CV",
"cs.AI",
"cs.CY",
"cs.MM"
] | The purpose of this paper is to contribute towards the near-future privacy-preserving big data analytical healthcare platforms, capable of processing streamed or uploaded timeseries data or videos from patients. The experimental work includes a real-life knee rehabilitation video dataset capturing a set of exercises fr... | {
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2412.20735 | HUNYUANPROVER: A Scalable Data Synthesis Framework and Guided Tree
Search for Automated Theorem Proving | [
"cs.AI",
"cs.CL"
] | We introduce HunyuanProver, an language model finetuned from the Hunyuan 7B for interactive automatic theorem proving with LEAN4. To alleviate the data sparsity issue, we design a scalable framework to iterative synthesize data with low cost. Besides, guided tree search algorithms are designed to enable effective ``sys... | {
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2412.20741 | Depression and Anxiety Prediction Using Deep Language Models and
Transfer Learning | [
"cs.CL"
] | Digital screening and monitoring applications can aid providers in the management of behavioral health conditions. We explore deep language models for detecting depression, anxiety, and their co-occurrence from conversational speech collected during 16k user interactions with an application. Labels come from PHQ-8 and ... | {
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2412.20742 | UniRS: Unifying Multi-temporal Remote Sensing Tasks through Vision
Language Models | [
"cs.CV"
] | The domain gap between remote sensing imagery and natural images has recently received widespread attention and Vision-Language Models (VLMs) have demonstrated excellent generalization performance in remote sensing multimodal tasks. However, current research is still limited in exploring how remote sensing VLMs handle ... | {
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2412.20744 | Advancing Parkinson's Disease Progression Prediction: Comparing Long
Short-Term Memory Networks and Kolmogorov-Arnold Networks | [
"cs.LG",
"cs.AI"
] | Parkinson's Disease (PD) is a degenerative neurological disorder that impairs motor and non-motor functions, significantly reducing quality of life and increasing mortality risk. Early and accurate detection of PD progression is vital for effective management and improved patient outcomes. Current diagnostic methods, h... | {
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2412.20749 | Solar Filaments Detection using Active Contours Without Edges | [
"cs.CV",
"astro-ph.IM",
"astro-ph.SR",
"cs.AI",
"cs.LG"
] | In this article, an active contours without edges (ACWE)-based algorithm has been proposed for the detection of solar filaments in H-alpha full-disk solar images. The overall algorithm consists of three main steps of image processing. These are image pre-processing, image segmentation, and image post-processing. Here i... | {
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2412.20750 | Are Vision-Language Models Truly Understanding Multi-vision Sensor? | [
"cs.CV"
] | Large-scale Vision-Language Models (VLMs) have advanced by aligning vision inputs with text, significantly improving performance in computer vision tasks. Moreover, for VLMs to be effectively utilized in real-world applications, an understanding of diverse multi-vision sensor data, such as thermal, depth, and X-ray inf... | {
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2412.20755 | Ultra-Wideband Double-Directional Channel Measurements and Statistical
Modeling in Urban Microcellular Environments for the Upper-Midband/FR3 | [
"eess.SY",
"cs.SY"
] | The upper midband, designated as Frequency Range 3 (FR3), is increasingly critical for the next-generation of wireless networks. Channel propagation measurements and their statistical analysis are essential first steps towards this direction. This paper presents a comprehensive ultra-wideband (UWB) double-directional c... | {
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2412.20756 | Unsupervised dense retrieval with conterfactual contrastive learning | [
"cs.IR"
] | Efficiently retrieving a concise set of candidates from a large document corpus remains a pivotal challenge in Information Retrieval (IR). Neural retrieval models, particularly dense retrieval models built with transformers and pretrained language models, have been popular due to their superior performance. However, cr... | {
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2412.20758 | High-Sensitivity Vision-Based Tactile Sensing Enhanced by
Microstructures and Lightweight CNN | [
"cs.RO",
"cs.HC"
] | Tactile sensing is critical in advanced interactive systems by emulating the human sense of touch to detect stimuli. Vision-based tactile sensors (VBTSs) are promising for their ability to provide rich information, robustness, adaptability, low cost, and multimodal capabilities. However, current technologies still have... | {
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2412.20760 | Attributing Culture-Conditioned Generations to Pretraining Corpora | [
"cs.CL",
"cs.AI"
] | In open-ended generative tasks like narrative writing or dialogue, large language models often exhibit cultural biases, showing limited knowledge and generating templated outputs for less prevalent cultures. Recent works show that these biases may stem from uneven cultural representation in pretraining corpora. This wo... | {
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2412.20761 | Unforgettable Lessons from Forgettable Images: Intra-Class Memorability
Matters in Computer Vision Tasks | [
"cs.CV"
] | We introduce intra-class memorability, where certain images within the same class are more memorable than others despite shared category characteristics. To investigate what features make one object instance more memorable than others, we design and conduct human behavior experiments, where participants are shown a ser... | {
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2412.20762 | Enhancing Privacy in Federated Learning through Quantum Teleportation
Integration | [
"quant-ph",
"cs.CR",
"cs.CY",
"cs.LG"
] | Federated learning enables collaborative model training across multiple clients without sharing raw data, thereby enhancing privacy. However, the exchange of model updates can still expose sensitive information. Quantum teleportation, a process that transfers quantum states between distant locations without physical tr... | {
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2412.20767 | KeyGS: A Keyframe-Centric Gaussian Splatting Method for Monocular Image
Sequences | [
"cs.CV",
"cs.AI"
] | Reconstructing high-quality 3D models from sparse 2D images has garnered significant attention in computer vision. Recently, 3D Gaussian Splatting (3DGS) has gained prominence due to its explicit representation with efficient training speed and real-time rendering capabilities. However, existing methods still heavily d... | {
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2412.20768 | Sample Correlation for Fingerprinting Deep Face Recognition | [
"cs.CV",
"cs.AI"
] | Face recognition has witnessed remarkable advancements in recent years, thanks to the development of deep learning techniques.However, an off-the-shelf face recognition model as a commercial service could be stolen by model stealing attacks, posing great threats to the rights of the model owner.Model fingerprinting, as... | {
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2412.20770 | Humanoid Robot RHP Friends: Seamless Combination of Autonomous and
Teleoperated Tasks in a Nursing Context | [
"cs.RO",
"cs.HC"
] | This paper describes RHP Friends, a social humanoid robot developed to enable assistive robotic deployments in human-coexisting environments. As a use-case application, we present its potential use in nursing by extending its capabilities to operate human devices and tools according to the task and by enabling remote a... | {
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2412.20771 | Optimally Decoding Two-Dimensional Reed-Solomon Codes up to the
Half-Singleton Bound | [
"cs.IT",
"math.IT"
] | Constructing Reed-Solomon (RS) codes capable of correcting insertion and deletion errors (ins-del errors) has been the focus of numerous recent studies. However, the development of efficient decoding algorithms for such RS codes has not garnered significant attention and remains an important and intriguing open problem... | {
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2412.20772 | Large Language Model Enabled Multi-Task Physical Layer Network | [
"cs.IT",
"eess.SP",
"math.IT"
] | The recent advance of Artificial Intelligence (AI) is continuously reshaping the future 6G wireless communications. Recently, the development of Large Language Models (LLMs) offers a promising approach to effectively improve the performance and generalization for different physical layer tasks. However, most existing w... | {
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2412.20784 | DEMO: A Dynamics-Enhanced Learning Model for Multi-Horizon Trajectory
Prediction in Autonomous Vehicles | [
"cs.RO"
] | Autonomous vehicles (AVs) rely on accurate trajectory prediction of surrounding vehicles to ensure the safety of both passengers and other road users. Trajectory prediction spans both short-term and long-term horizons, each requiring distinct considerations: short-term predictions rely on accurately capturing the vehic... | {
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2412.20785 | Accelerating Energy-Efficient Federated Learning in Cell-Free Networks
with Adaptive Quantization | [
"cs.LG"
] | Federated Learning (FL) enables clients to share learning parameters instead of local data, reducing communication overhead. Traditional wireless networks face latency challenges with FL. In contrast, Cell-Free Massive MIMO (CFmMIMO) can serve multiple clients on shared resources, boosting spectral efficiency and reduc... | {
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2412.20787 | SecBench: A Comprehensive Multi-Dimensional Benchmarking Dataset for
LLMs in Cybersecurity | [
"cs.CR",
"cs.AI"
] | Evaluating Large Language Models (LLMs) is crucial for understanding their capabilities and limitations across various applications, including natural language processing and code generation. Existing benchmarks like MMLU, C-Eval, and HumanEval assess general LLM performance but lack focus on specific expert domains su... | {
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2412.20788 | An Experimental Study of Passive UAV Tracking with Digital Arrays and
Cellular Downlink Signals | [
"eess.SP",
"cs.SY",
"eess.SY"
] | Given the prospects of the low-altitude economy (LAE) and the popularity of unmanned aerial vehicles (UAVs), there are increasing demands on monitoring flying objects at low altitude in wide urban areas. In this work, the widely deployed long-term evolution (LTE) base station (BS) is exploited to illuminate UAVs in bis... | {
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2412.20790 | Frequency-Masked Embedding Inference: A Non-Contrastive Approach for
Time Series Representation Learning | [
"cs.LG",
"cs.AI"
] | Contrastive learning underpins most current self-supervised time series representation methods. The strategy for constructing positive and negative sample pairs significantly affects the final representation quality. However, due to the continuous nature of time series semantics, the modeling approach of contrastive le... | {
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2412.20796 | FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours
with 32 GPUs | [
"cs.DC",
"cs.LG"
] | Graph neural network universal interatomic potentials (GNN-UIPs) have demonstrated remarkable generalization and transfer capabilities in material discovery and property prediction. These models can accelerate molecular dynamics (MD) simulation by several orders of magnitude while maintaining \textit{ab initio} accurac... | {
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2412.20798 | A Tale of Two Imperatives: Privacy and Explainability | [
"cs.CR",
"cs.AI",
"cs.CV"
] | Deep learning's preponderance across scientific domains has reshaped high-stakes decision-making, making it essential to follow rigorous operational frameworks that include both Right-to-Privacy (RTP) and Right-to-Explanation (RTE). This paper examines the complexities of combining these two requirements. For RTP, we f... | {
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2412.20800 | VMix: Improving Text-to-Image Diffusion Model with Cross-Attention
Mixing Control | [
"cs.CV"
] | While diffusion models show extraordinary talents in text-to-image generation, they may still fail to generate highly aesthetic images. More specifically, there is still a gap between the generated images and the real-world aesthetic images in finer-grained dimensions including color, lighting, composition, etc. In thi... | {
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2412.20801 | Generalize Your Face Forgery Detectors: An Insertable Adaptation Module
Is All You Need | [
"cs.CV"
] | A plethora of face forgery detectors exist to tackle facial deepfake risks. However, their practical application is hindered by the challenge of generalizing to forgeries unseen during the training stage. To this end, we introduce an insertable adaptation module that can adapt a trained off-the-shelf detector using onl... | {
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2412.20802 | Robust Matrix Completion for Discrete Rating-Scale Data | [
"stat.ML",
"cs.LG",
"stat.CO",
"stat.ME"
] | Matrix completion has gained considerable interest in recent years. The goal of matrix completion is to predict the unknown entries of a partially observed matrix using its known entries. Although common applications feature discrete rating-scale data, such as user-product rating matrices in recommender systems or surv... | {
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2412.20803 | Frequency-aware Event Cloud Network | [
"cs.CV"
] | Event cameras are biologically inspired sensors that emit events asynchronously with remarkable temporal resolution, garnering significant attention from both industry and academia. Mainstream methods favor frame and voxel representations, which reach a satisfactory performance while introducing time-consuming transfor... | {
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2412.20806 | LEO Satellite-Enabled Random Access with Large Differential Delay and
Doppler Shift | [
"cs.IT",
"eess.SP",
"math.IT"
] | This paper investigates joint device identification, channel estimation, and symbol detection for LEO satellite-enabled grant-free random access systems, specifically targeting scenarios where remote Internet-of-Things (IoT) devices operate without global navigation satellite system (GNSS) assistance. Considering the c... | {
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2412.20807 | Two Heads Are Better Than One: Averaging along Fine-Tuning to Improve
Targeted Transferability | [
"cs.CV",
"cs.AI"
] | With much longer optimization time than that of untargeted attacks notwithstanding, the transferability of targeted attacks is still far from satisfactory. Recent studies reveal that fine-tuning an existing adversarial example (AE) in feature space can efficiently boost its targeted transferability. However, existing f... | {
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2412.20810 | TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series
Forecasting | [
"cs.LG"
] | Time series forecasting plays a crucial role in data mining, driving rapid advancements across numerous industries. With the emergence of large models, time series foundation models (TSFMs) have exhibited remarkable generalization capabilities, such as zero-shot learning, through large-scale pre-training. Meanwhile, Re... | {
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2412.20816 | Length-Aware DETR for Robust Moment Retrieval | [
"cs.CV",
"cs.AI"
] | Video Moment Retrieval (MR) aims to localize moments within a video based on a given natural language query. Given the prevalent use of platforms like YouTube for information retrieval, the demand for MR techniques is significantly growing. Recent DETR-based models have made notable advances in performance but still st... | {
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2412.20821 | Enhancing Multimodal Emotion Recognition through Multi-Granularity
Cross-Modal Alignment | [
"eess.AS",
"cs.CL",
"cs.SD"
] | Multimodal emotion recognition (MER), leveraging speech and text, has emerged as a pivotal domain within human-computer interaction, demanding sophisticated methods for effective multimodal integration. The challenge of aligning features across these modalities is significant, with most existing approaches adopting a s... | {
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2412.20822 | Fine-Tuning TransMorph with Gradient Correlation for Anatomical
Alignment | [
"eess.IV",
"cs.AI",
"cs.CV"
] | Unsupervised deep learning is a promising method in brain MRI registration to reduce the reliance on anatomical labels, while still achieving anatomically accurate transformations. For the Learn2Reg2024 LUMIR challenge, we propose fine-tuning of the pre-trained TransMorph model to improve the convergence stability as w... | {
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2412.20824 | Isoperimetry is All We Need: Langevin Posterior Sampling for RL with
Sublinear Regret | [
"cs.LG",
"stat.ML"
] | Common assumptions, like linear or RKHS models, and Gaussian or log-concave posteriors over the models, do not explain practical success of RL across a wider range of distributions and models. Thus, we study how to design RL algorithms with sublinear regret for isoperimetric distributions, specifically the ones satisfy... | {
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2412.20826 | ReStory: VLM-augmentation of Social Human-Robot Interaction Datasets | [
"cs.RO",
"cs.HC"
] | Internet-scaled datasets are a luxury for human-robot interaction (HRI) researchers, as collecting natural interaction data in the wild is time-consuming and logistically challenging. The problem is exacerbated by robots' different form factors and interaction modalities. Inspired by recent work on ethnomethodological ... | {
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2412.20828 | Effective Application of Normalized Min-Sum Decoding for BCH Codes | [
"cs.IT",
"math.IT"
] | High-throughput decoding of BCH codes necessitates efficient and parallelizable decoders. However, the algebraic rigidity of BCH codes poses significant challenges to applying parallel belief propagation variants. To address this, we propose a systematic design scheme for constructing parity-check matrices using a heur... | {
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2412.20830 | ReFlow6D: Refraction-Guided Transparent Object 6D Pose Estimation via
Intermediate Representation Learning | [
"cs.CV",
"cs.RO"
] | Transparent objects are ubiquitous in daily life, making their perception and robotics manipulation important. However, they present a major challenge due to their distinct refractive and reflective properties when it comes to accurately estimating the 6D pose. To solve this, we present ReFlow6D, a novel method for tra... | {
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2412.20833 | Inclusion 2024 Global Multimedia Deepfake Detection: Towards
Multi-dimensional Facial Forgery Detection | [
"cs.CV",
"cs.MM"
] | In this paper, we present the Global Multimedia Deepfake Detection held concurrently with the Inclusion 2024. Our Multimedia Deepfake Detection aims to detect automatic image and audio-video manipulations including but not limited to editing, synthesis, generation, Photoshop,etc. Our challenge has attracted 1500 teams ... | {
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2412.20834 | Disentangling Preference Representation and Text Generation for
Efficient Individual Preference Alignment | [
"cs.CL",
"cs.AI"
] | Aligning Large Language Models (LLMs) with general human preferences has been proved crucial in improving the interaction quality between LLMs and human. However, human values are inherently diverse among different individuals, making it insufficient to align LLMs solely with general preferences. To address this, perso... | {
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2412.20838 | Dual-Space Augmented Intrinsic-LoRA for Wind Turbine Segmentation | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Accurate segmentation of wind turbine blade (WTB) images is critical for effective assessments, as it directly influences the performance of automated damage detection systems. Despite advancements in large universal vision models, these models often underperform in domain-specific tasks like WTB segmentation. To addre... | {
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2412.20844 | Acquisition-Independent Deep Learning for Quantitative MRI Parameter
Estimation using Neural Controlled Differential Equations | [
"physics.med-ph",
"cs.LG"
] | Deep learning has proven to be a suitable alternative to least-squares (LSQ) fitting for parameter estimation in various quantitative MRI (QMRI) models. However, current deep learning implementations are not robust to changes in MR acquisition protocols. In practice, QMRI acquisition protocols differ substantially betw... | {
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2412.20845 | Data-Based Efficient Off-Policy Stabilizing Optimal Control Algorithms
for Discrete-Time Linear Systems via Damping Coefficients | [
"eess.SY",
"cs.SY"
] | Policy iteration is one of the classical frameworks of reinforcement learning, which requires a known initial stabilizing control. However, finding the initial stabilizing control depends on the known system model. To relax this requirement and achieve model-free optimal control, in this paper, two different reinforcem... | {
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2412.20846 | Are LLMs Really Not Knowledgable? Mining the Submerged Knowledge in
LLMs' Memory | [
"cs.CL"
] | Large language models (LLMs) have shown promise as potential knowledge bases, yet they often struggle with question-answering tasks and are prone to hallucinations. While previous research attributes these issues to knowledge gaps in the model's parameters, our investigation reveals a different phenomenon: LLMs often r... | {
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2412.20848 | Analog Alchemy: Neural Computation with In-Memory Inference, Learning
and Routing | [
"cs.NE",
"cs.AI",
"cs.ET"
] | As neural computation is revolutionizing the field of Artificial Intelligence (AI), rethinking the ideal neural hardware is becoming the next frontier. Fast and reliable von Neumann architecture has been the hosting platform for neural computation. Although capable, its separation of memory and computation creates the ... | {
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2412.20851 | About rectified sigmoid function for enhancing the accuracy of
Physics-Informed Neural Networks | [
"math.NA",
"cs.AI",
"cs.LG",
"cs.NA",
"physics.comp-ph"
] | The article is devoted to the study of neural networks with one hidden layer and a modified activation function for solving physical problems. A rectified sigmoid activation function has been proposed to solve physical problems described by the ODE with neural networks. Algorithms for physics-informed data-driven initi... | {
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2412.20864 | Enhancing Annotated Bibliography Generation with LLM Ensembles | [
"cs.CL",
"cs.AI",
"cs.LG"
] | This work proposes a novel approach to enhancing annotated bibliography generation through Large Language Model (LLM) ensembles. In particular, multiple LLMs in different roles -- controllable text generation, evaluation, and summarization -- are introduced and validated using a systematic methodology to enhance model ... | {
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2412.20867 | Holistic Construction Automation with Modular Robots: From High-Level
Task Specification to Execution | [
"cs.RO",
"cs.AI",
"cs.HC"
] | In situ robotic automation in construction is challenging due to constantly changing environments, a shortage of robotic experts, and a lack of standardized frameworks bridging robotics and construction practices. This work proposes a holistic framework for construction task specification, optimization of robot morphol... | {
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2412.20868 | Machine Learning of Slow Collective Variables and Enhanced Sampling via
Spatial Techniques | [
"physics.chem-ph",
"cs.LG"
] | Understanding the long-time dynamics of complex physical processes depends on our ability to recognize patterns. To simplify the description of these processes, we often introduce a set of reaction coordinates, customarily referred to as collective variables (CVs). The quality of these CVs heavily impacts our comprehen... | {
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2412.20870 | SoftPatch+: Fully Unsupervised Anomaly Classification and Segmentation | [
"cs.CV"
] | Although mainstream unsupervised anomaly detection (AD) (including image-level classification and pixel-level segmentation)algorithms perform well in academic datasets, their performance is limited in practical application due to the ideal experimental setting of clean training data. Training with noisy data is an inev... | {
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2412.20871 | Simplified integrity checking for an expressive class of denial
constraints | [
"cs.DB"
] | Data integrity is crucial for ensuring data correctness and quality, maintained through integrity constraints that must be continuously checked, especially in data-intensive systems like OLTP. While DBMSs handle common constraints well, complex constraints often require ad-hoc solutions. Research since the 1980s has fo... | {
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2412.20872 | LINK: Adaptive Modality Interaction for Audio-Visual Video Parsing | [
"cs.CV"
] | Audio-visual video parsing focuses on classifying videos through weak labels while identifying events as either visible, audible, or both, alongside their respective temporal boundaries. Many methods ignore that different modalities often lack alignment, thereby introducing extra noise during modal interaction. In this... | {
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2412.20875 | Attention Is All You Need For Mixture-of-Depths Routing | [
"cs.CV"
] | Advancements in deep learning are driven by training models with increasingly larger numbers of parameters, which in turn heightens the computational demands. To address this issue, Mixture-of-Depths (MoD) models have been proposed to dynamically assign computations only to the most relevant parts of the inputs, thereb... | {
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2412.20881 | LiDAR-Camera Fusion for Video Panoptic Segmentation without Video
Training | [
"cs.CV"
] | Panoptic segmentation, which combines instance and semantic segmentation, has gained a lot of attention in autonomous vehicles, due to its comprehensive representation of the scene. This task can be applied for cameras and LiDAR sensors, but there has been a limited focus on combining both sensors to enhance image pano... | {
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2412.20885 | CF-CGN: Channel Fingerprints Extrapolation for Multi-band Massive MIMO
Transmission based on Cycle-Consistent Generative Networks | [
"cs.IT",
"cs.LG",
"eess.SP",
"math.IT"
] | Multi-band massive multiple-input multiple-output (MIMO) communication can promote the cooperation of licensed and unlicensed spectra, effectively enhancing spectrum efficiency for Wi-Fi and other wireless systems. As an enabler for multi-band transmission, channel fingerprints (CF), also known as the channel knowledge... | {
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2412.20888 | Navigating Chemical-Linguistic Sharing Space with Heterogeneous
Molecular Encoding | [
"cs.CE"
] | Chemical language models (CLMs) are prominent for their effectiveness in exploring chemical space and enabling molecular engineering. However, while exploring chemical-linguistic space, CLMs suffer from the gap between natural language and molecular representations. This challenge is primarily due to the inherent model... | {
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2412.20891 | DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models | [
"cs.CL",
"cs.LG"
] | Low-rank adaptation (LoRA) reduces the computational and memory demands of fine-tuning large language models (LLMs) by approximating updates with low-rank matrices. However, low-rank approximation in two-dimensional space fails to capture high-dimensional structures within the target matrix. Recently, tensor decomposit... | {
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} |
2412.20892 | Rethinking Aleatoric and Epistemic Uncertainty | [
"cs.LG",
"stat.ML"
] | The ideas of aleatoric and epistemic uncertainty are widely used to reason about the probabilistic predictions of machine-learning models. We identify incoherence in existing discussions of these ideas and suggest this stems from the aleatoric-epistemic view being insufficiently expressive to capture all of the distinc... | {
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} |
2412.20895 | Towards Compatible Fine-tuning for Vision-Language Model Updates | [
"cs.CV",
"cs.LG"
] | So far, efficient fine-tuning has become a popular strategy for enhancing the capabilities of foundation models on downstream tasks by learning plug-and-play modules. However, existing methods overlook a crucial issue: if the underlying foundation model is updated, are these plug-and-play modules still effective? In th... | {
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} |
2412.20899 | DDIM sampling for Generative AIBIM, a faster intelligent structural
design framework | [
"cs.CV",
"cs.LG"
] | Generative AIBIM, a successful structural design pipeline, has proven its ability to intelligently generate high-quality, diverse, and creative shear wall designs that are tailored to specific physical conditions. However, the current module of Generative AIBIM that generates designs, known as the physics-based conditi... | {
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} |
2412.20901 | ILDiff: Generate Transparent Animated Stickers by Implicit Layout
Distillation | [
"cs.CV",
"cs.AI"
] | High-quality animated stickers usually contain transparent channels, which are often ignored by current video generation models. To generate fine-grained animated transparency channels, existing methods can be roughly divided into video matting algorithms and diffusion-based algorithms. The methods based on video matti... | {
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} |
2412.20903 | WalkVLM:Aid Visually Impaired People Walking by Vision Language Model | [
"cs.CV",
"cs.AI"
] | Approximately 200 million individuals around the world suffer from varying degrees of visual impairment, making it crucial to leverage AI technology to offer walking assistance for these people. With the recent progress of vision-language models (VLMs), employing VLMs to improve this field has emerged as a popular rese... | {
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} |
2412.20911 | TiGDistill-BEV: Multi-view BEV 3D Object Detection via Target
Inner-Geometry Learning Distillation | [
"cs.CV"
] | Accurate multi-view 3D object detection is essential for applications such as autonomous driving. Researchers have consistently aimed to leverage LiDAR's precise spatial information to enhance camera-based detectors through methods like depth supervision and bird-eye-view (BEV) feature distillation. However, existing a... | {
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} |
2412.20914 | Language-based Audio Retrieval with Co-Attention Networks | [
"cs.SD",
"cs.IR",
"eess.AS"
] | In recent years, user-generated audio content has proliferated across various media platforms, creating a growing need for efficient retrieval methods that allow users to search for audio clips using natural language queries. This task, known as language-based audio retrieval, presents significant challenges due to the... | {
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} |
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