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2caaba9d59f72d5a3bb8a562dc2a029e01d6f7529bc3e4dc1e8af7d006c14feb | 2026-01-01T00:00:00-05:00 | From artificial to circular intelligence to support the well-being of our habitat | arXiv:2512.24131v1 Announce Type: new Abstract: The proliferation of machine learning and artificial intelligence redefines the interaction between the anthropogenic and natural elements of our habitat.The use of monitoring tools, processing facilities and the internet of things supports the assessment of planetary hea... | https://arxiv.org/abs/2512.24131 | Academic Papers | svg |
2ae37c1c67d7c498ca964703ce1eb427c7fe3bb82d79653131eedd675b3a3b55 | 2026-01-01T00:00:00-05:00 | From FPT Decision to FPT Enumeration | arXiv:2512.24137v1 Announce Type: new Abstract: Fixed-parameter tractable (FPT) algorithms have been successfully applied to many intractable problems -- with a focus on decision and optimization problems. Their aim is to confine the exponential explosion to some parameter, while the time complexity only depends polyno... | https://arxiv.org/abs/2512.24137 | Academic Papers | svg |
b15b7d579cbe53a2b61c06f6ce9a7ae22db348917b69a00363081d3b6cd1ce6b | 2026-01-01T00:00:00-05:00 | GARDO: Reinforcing Diffusion Models without Reward Hacking | arXiv:2512.24138v1 Announce Type: new Abstract: Fine-tuning diffusion models via online reinforcement learning (RL) has shown great potential for enhancing text-to-image alignment. However, since precisely specifying a ground-truth objective for visual tasks remains challenging, the models are often optimized using a p... | https://arxiv.org/abs/2512.24138 | Academic Papers | svg |
284a2d0aebf445c39451e31d5e22399a74734016555d8a5919649ff28aa5bb02 | 2026-01-01T00:00:00-05:00 | Colorful Pinball: Density-Weighted Quantile Regression for Conditional Guarantee of Conformal Prediction | arXiv:2512.24139v1 Announce Type: new Abstract: While conformal prediction provides robust marginal coverage guarantees, achieving reliable conditional coverage for specific inputs remains challenging. Although exact distribution-free conditional coverage is impossible with finite samples, recent work has focused on im... | https://arxiv.org/abs/2512.24139 | Academic Papers | svg |
ccc352116fdbac6eced3b8b5b68f7d6280c50f6d07a72d4947feb2d77bd47b2a | 2026-01-01T00:00:00-05:00 | Environmental Sound Deepfake Detection Challenge: An Overview | arXiv:2512.24140v1 Announce Type: new Abstract: Recent progress in audio generation models has made it possible to create highly realistic and immersive soundscapes, which are now widely used in film and virtual-reality-related applications. However, these audio generators also raise concerns about potential misuse, su... | https://arxiv.org/abs/2512.24140 | Academic Papers | svg |
dfeef0faa914052954d5607f9bc7964e54476ba2f141c084d0254d4f15e1601c | 2026-01-01T00:00:00-05:00 | Activation Steering for Masked Diffusion Language Models | arXiv:2512.24143v1 Announce Type: new Abstract: Masked diffusion language models (MDLMs) generate text through an iterative denoising process. They have recently gained attention due to mask-parallel decoding and competitive performance with autoregressive large language models. However, effective mechanisms for infere... | https://arxiv.org/abs/2512.24143 | Academic Papers | svg |
73f7b2121cf18c6e5310300694dc4688488fe1f71a9e194bc7317a3305527f08 | 2026-01-01T00:00:00-05:00 | Paired Seed Evaluation: Statistical Reliability for Learning-Based Simulators | arXiv:2512.24145v1 Announce Type: new Abstract: Machine learning systems appear stochastic but are deterministically random, as seeded pseudorandom number generators produce identical realisations across executions. Learning-based simulators are widely used to compare algorithms, design choices, and interventions under... | https://arxiv.org/abs/2512.24145 | Academic Papers | svg |
3311ac0ad1779eaff4ca2095d037dd25b8123e089310555c5dc2117348ae927f | 2026-01-01T00:00:00-05:00 | Taming Preference Mode Collapse via Directional Decoupling Alignment in Diffusion Reinforcement Learning | arXiv:2512.24146v1 Announce Type: new Abstract: Recent studies have demonstrated significant progress in aligning text-to-image diffusion models with human preference via Reinforcement Learning from Human Feedback. However, while existing methods achieve high scores on automated reward metrics, they often lead to Prefe... | https://arxiv.org/abs/2512.24146 | Academic Papers | svg |
84fb323e5268d5b68be86568795613d3e2b0ce4e646b10da24b3011ec8f072ca | 2026-01-01T00:00:00-05:00 | Large Emotional World Model | arXiv:2512.24149v1 Announce Type: new Abstract: World Models serve as tools for understanding the current state of the world and predicting its future dynamics, with broad application potential across numerous fields. As a key component of world knowledge, emotion significantly influences human decision-making. While e... | https://arxiv.org/abs/2512.24149 | Academic Papers | svg |
dbb42184195853c9d6a87b0266cb9dd7518ff7c8bea4f32c1d82bee4c3118130 | 2026-01-01T00:00:00-05:00 | Graph-Based Exploration for ARC-AGI-3 Interactive Reasoning Tasks | arXiv:2512.24156v1 Announce Type: new Abstract: We present a training-free graph-based approach for solving interactive reasoning tasks in the ARC-AGI-3 benchmark. ARC-AGI-3 comprises game-like tasks where agents must infer task mechanics through limited interactions, and adapt to increasing complexity as levels progre... | https://arxiv.org/abs/2512.24156 | Academic Papers | svg |
7b5a0b7c437cfa4a6472ecaf6da0e227c9d175b682c5ca90c820b9c7d4280623 | 2026-01-01T00:00:00-05:00 | Training Report of TeleChat3-MoE | arXiv:2512.24157v1 Announce Type: new Abstract: TeleChat3-MoE is the latest series of TeleChat large language models, featuring a Mixture-of-Experts (MoE) architecture with parameter counts ranging from 105 billion to over one trillion,trained end-to-end on Ascend NPU cluster. This technical report mainly presents the ... | https://arxiv.org/abs/2512.24157 | Academic Papers | svg |
e00d423542f48dcacbc268c77e2344b9c23b4b9363b6b1d42de42ba645f16b42 | 2026-01-01T00:00:00-05:00 | Developing controlled natural language for formal specification patterns using AI assistants | arXiv:2512.24159v1 Announce Type: new Abstract: Using an AI assistant, we developed a method for systematically constructing controlled natural language for requirements based on formal specification patterns containing logical attributes. The method involves three stages: 1) compiling a generalized natural language re... | https://arxiv.org/abs/2512.24159 | Academic Papers | svg |
579bcc2f80224a4479947d58f4aba51da30429e96cb2029cbb531082b0baf194 | 2026-01-01T00:00:00-05:00 | Towards Open-Vocabulary Industrial Defect Understanding with a Large-Scale Multimodal Dataset | arXiv:2512.24160v1 Announce Type: new Abstract: We present IMDD-1M, the first large-scale Industrial Multimodal Defect Dataset comprising 1,000,000 aligned image-text pairs, designed to advance multimodal learning for manufacturing and quality inspection. IMDD-1M contains high-resolution real-world defects spanning ove... | https://arxiv.org/abs/2512.24160 | Academic Papers | svg |
47bc5265511d59ab464455df7d4593ca9ebb45acab04a6bba3605a9d8e3384ea | 2026-01-01T00:00:00-05:00 | Bayesian Self-Distillation for Image Classification | arXiv:2512.24162v1 Announce Type: new Abstract: Supervised training of deep neural networks for classification typically relies on hard targets, which promote overconfidence and can limit calibration, generalization, and robustness. Self-distillation methods aim to mitigate this by leveraging inter-class and sample-spe... | https://arxiv.org/abs/2512.24162 | Academic Papers | svg |
05818c9990aa54196b8f7e480e4b825a69940e559e372b6c40fe1c6f077adc92 | 2026-01-01T00:00:00-05:00 | DiffThinker: Towards Generative Multimodal Reasoning with Diffusion Models | arXiv:2512.24165v1 Announce Type: new Abstract: While recent Multimodal Large Language Models (MLLMs) have attained significant strides in multimodal reasoning, their reasoning processes remain predominantly text-centric, leading to suboptimal performance in complex long-horizon, vision-centric tasks. In this paper, we... | https://arxiv.org/abs/2512.24165 | Academic Papers | svg |
a32f0b47bbb320cb38673c1ab617346a2c962831bc33d2407aa5ba6c93ca966d | 2026-01-01T00:00:00-05:00 | External Human-Machine Interface based on Intent Recognition: Framework Design and Experimental Validation | arXiv:2512.24166v1 Announce Type: new Abstract: Increasing autonomous vehicles (AVs) in transportation systems makes effective interactions between AVs and pedestrians indispensable. External human--machine interface (eHMI), which employs visual or auditory cues to explicitly convey vehicle behaviors can compensate for... | https://arxiv.org/abs/2512.24166 | Academic Papers | svg |
0beb86a098c6b01904d89c9fce0959bad923594fae46f7ad25c374f0f42754bc | 2026-01-01T00:00:00-05:00 | Hybrid Voltage and Current Control Method for Harmonic Mitigation of Single-Phase AC Loads in DC Microgrids | arXiv:2512.24170v1 Announce Type: new Abstract: DC microgrids provide an efficient framework for the interconnection of DC distributed energy resources (DERs) and DC loads. To continue to supply legacy single-phase AC loads, DC/AC converters can be integrated in the DC microgrid. The oscillatory instantaneous power of ... | https://arxiv.org/abs/2512.24170 | Academic Papers | svg |
7cd76fb1731cc47e2b52c4c8b7c9d90ee247e7becc9e23478c827faf17776a90 | 2026-01-01T00:00:00-05:00 | Deep Global Clustering for Hyperspectral Image Segmentation: Concepts, Applications, and Open Challenges | arXiv:2512.24172v1 Announce Type: new Abstract: Hyperspectral imaging (HSI) analysis faces computational bottlenecks due to massive data volumes that exceed available memory. While foundation models pre-trained on large remote sensing datasets show promise, their learned representations often fail to transfer to domain... | https://arxiv.org/abs/2512.24172 | Academic Papers | svg |
daa18822db4934674b13e701d28fbe2552417a492f70cd42478c7a156f82f9f2 | 2026-01-01T00:00:00-05:00 | Guiding a Diffusion Transformer with the Internal Dynamics of Itself | arXiv:2512.24176v1 Announce Type: new Abstract: The diffusion model presents a powerful ability to capture the entire (conditional) data distribution. However, due to the lack of sufficient training and data to learn to cover low-probability areas, the model will be penalized for failing to generate high-quality images... | https://arxiv.org/abs/2512.24176 | Academic Papers | svg |
86c34032bc23baa3b728d53f8439cf4fe3526aba01e026facee9e4b8046e5f61 | 2026-01-01T00:00:00-05:00 | Now or Never: Continuous Surveillance AIoT System for Ephemeral Events in Intermittent Sensor Networks | arXiv:2512.24179v1 Announce Type: new Abstract: Wilderness monitoring tasks, such as poaching surveillance and forest fire detection, require pervasive and high-accuracy sensing. While AIoT offers a promising path, covering vast, inaccessible regions necessitates the massive deployment of maintenance-free, battery-less... | https://arxiv.org/abs/2512.24179 | Academic Papers | svg |
6ad52b1d3f6abd0422e7966f0c59c3f9013ae6ed94725e3d6cd6120109cd26d6 | 2026-01-01T00:00:00-05:00 | MedKGI: Iterative Differential Diagnosis with Medical Knowledge Graphs and Information-Guided Inquiring | arXiv:2512.24181v1 Announce Type: new Abstract: Recent advancements in Large Language Models (LLMs) have demonstrated significant promise in clinical diagnosis. However, current models struggle to emulate the iterative, diagnostic hypothesis-driven reasoning of real clinical scenarios. Specifically, current LLMs suffer... | https://arxiv.org/abs/2512.24181 | Academic Papers | svg |
e6c67ad10ee6247bc5182e0fd137af9b9d494cab2f631c00e0b568e7dda5ccec | 2026-01-01T00:00:00-05:00 | CoHalLo: code hallucination localization via probing hidden layer vector | arXiv:2512.24183v1 Announce Type: new Abstract: The localization of code hallucinations aims to identify specific lines of code containing hallucinations, helping developers to improve the reliability of AI-generated code more efficiently. Although recent studies have adopted several methods to detect code hallucinatio... | https://arxiv.org/abs/2512.24183 | Academic Papers | svg |
7e67b7725d536a7bf786be8289989a37f1d4e962e0015b5d3abf41f4114ad765 | 2026-01-01T00:00:00-05:00 | SCP: Accelerating Discovery with a Global Web of Autonomous Scientific Agents | arXiv:2512.24189v1 Announce Type: new Abstract: We introduce SCP: the Science Context Protocol, an open-source standard designed to accelerate discovery by enabling a global network of autonomous scientific agents. SCP is built on two foundational pillars: (1) Unified Resource Integration: At its core, SCP provides a u... | https://arxiv.org/abs/2512.24189 | Academic Papers | svg |
30248221d48d96dc676416d9a2794950c5ee24d718f523b6de32d95e28d17014 | 2026-01-01T00:00:00-05:00 | PointRAFT: 3D deep learning for high-throughput prediction of potato tuber weight from partial point clouds | arXiv:2512.24193v1 Announce Type: new Abstract: Potato yield is a key indicator for optimizing cultivation practices in agriculture. Potato yield can be estimated on harvesters using RGB-D cameras, which capture three-dimensional (3D) information of individual tubers moving along the conveyor belt. However, point cloud... | https://arxiv.org/abs/2512.24193 | Academic Papers | svg |
2f7f071d0ddf3b93305ac497b0b9133549448eddfaace6e202a70ed6939c366c | 2026-01-01T00:00:00-05:00 | CorGi: Contribution-Guided Block-Wise Interval Caching for Training-Free Acceleration of Diffusion Transformers | arXiv:2512.24195v1 Announce Type: new Abstract: Diffusion transformer (DiT) achieves remarkable performance in visual generation, but its iterative denoising process combined with larger capacity leads to a high inference cost. Recent works have demonstrated that the iterative denoising process of DiT models involves s... | https://arxiv.org/abs/2512.24195 | Academic Papers | svg |
8c12bc464c4ac6e6fc27831a51043c52429886fdbca947bf2afebae137377e4b | 2026-01-01T00:00:00-05:00 | PartMotionEdit: Fine-Grained Text-Driven 3D Human Motion Editing via Part-Level Modulation | arXiv:2512.24200v1 Announce Type: new Abstract: Existing text-driven 3D human motion editing methods have demonstrated significant progress, but are still difficult to precisely control over detailed, part-specific motions due to their global modeling nature. In this paper, we propose PartMotionEdit, a novel fine-grain... | https://arxiv.org/abs/2512.24200 | Academic Papers | svg |
11fa794eb3f2bdaa60c2b8543124221a2db5ce2d83a69633ff858b35f2c9a995 | 2026-01-01T00:00:00-05:00 | BATISNet: Instance Segmentation of Tooth Point Clouds with Boundary Awareness | arXiv:2512.24201v1 Announce Type: new Abstract: Accurate segmentation of the tooth point cloud is of great significance for diagnosis clinical assisting and treatment planning. Existing methods mostly employ semantic segmentation, focusing on the semantic feature between different types of teeth. However, due to the ti... | https://arxiv.org/abs/2512.24201 | Academic Papers | svg |
c2b5a55509ea7ddbba706d5db4f87cb7e578592e4a55a50e6e783908b4f2a271 | 2026-01-01T00:00:00-05:00 | Micro-Macro Tensor Neural Surrogates for Uncertainty Quantification in Collisional Plasma | arXiv:2512.24205v1 Announce Type: new Abstract: Plasma kinetic equations exhibit pronounced sensitivity to microscopic perturbations in model parameters and data, making reliable and efficient uncertainty quantification (UQ) essential for predictive simulations. However, the cost of uncertainty sampling, the high-dimen... | https://arxiv.org/abs/2512.24205 | Academic Papers | svg |
10479f957b8dbd64ae1ed9ab91650ffb4277ae5dbe531c4c76278d65f558eadb | 2026-01-01T00:00:00-05:00 | GR-Dexter Technical Report | arXiv:2512.24210v1 Announce Type: new Abstract: Vision-language-action (VLA) models have enabled language-conditioned, long-horizon robot manipulation, but most existing systems are limited to grippers. Scaling VLA policies to bimanual robots with high degree-of-freedom (DoF) dexterous hands remains challenging due to ... | https://arxiv.org/abs/2512.24210 | Academic Papers | svg |
a8bb78a9af8d5deef72bfd3ef4382573a14f73a68cf1d61f082bf49d3931ce25 | 2026-01-01T00:00:00-05:00 | RANGER: A Monocular Zero-Shot Semantic Navigation Framework through Contextual Adaptation | arXiv:2512.24212v1 Announce Type: new Abstract: Efficiently finding targets in complex environments is fundamental to real-world embodied applications. While recent advances in multimodal foundation models have enabled zero-shot object goal navigation, allowing robots to search for arbitrary objects without fine-tuning... | https://arxiv.org/abs/2512.24212 | Academic Papers | svg |
628029dab96362daf41595b449a438865de474a538047289564647435b4f2936 | 2026-01-01T00:00:00-05:00 | Medical Image Classification on Imbalanced Data Using ProGAN and SMA-Optimized ResNet: Application to COVID-19 | arXiv:2512.24214v1 Announce Type: new Abstract: The challenge of imbalanced data is prominent in medical image classification. This challenge arises when there is a significant disparity in the number of images belonging to a particular class, such as the presence or absence of a specific disease, as compared to the nu... | https://arxiv.org/abs/2512.24214 | Academic Papers | svg |
fb8eff06d093958cabcf95d29304f462a6198a92ca8177a6a94587491bcfd209 | 2026-01-01T00:00:00-05:00 | Efficient Decoding of Twisted GRS Codes and Roth--Lempel Codes | arXiv:2512.24217v1 Announce Type: new Abstract: MDS codes play a central role in practice due to their broad applications. To date, most known MDS codes are generalized Reed-Solomon (GRS) codes, leaving codes that are not equivalent to GRS codes comparatively less understood. Studying this non-GRS regime is therefore o... | https://arxiv.org/abs/2512.24217 | Academic Papers | svg |
2c3d535eb5631451029a8e9649930fae218d854215bbfbf18bd529350cc5444e | 2026-01-01T00:00:00-05:00 | ARM: A Learnable, Plug-and-Play Module for CLIP-based Open-vocabulary Semantic Segmentation | arXiv:2512.24224v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) is fundamentally hampered by the coarse, image-level representations of CLIP, which lack precise pixel-level details. Existing training-free methods attempt to resolve this by either importing priors from costly external founda... | https://arxiv.org/abs/2512.24224 | Academic Papers | svg |
2c1753e16bcf881ade319cec1788e116a93fa8fde709f21041c4abe1ce25d207 | 2026-01-01T00:00:00-05:00 | Mirage: One-Step Video Diffusion for Photorealistic and Coherent Asset Editing in Driving Scenes | arXiv:2512.24227v1 Announce Type: new Abstract: Vision-centric autonomous driving systems rely on diverse and scalable training data to achieve robust performance. While video object editing offers a promising path for data augmentation, existing methods often struggle to maintain both high visual fidelity and temporal... | https://arxiv.org/abs/2512.24227 | Academic Papers | svg |
06fa5e84a873e8944beb6d540942285dc05bdb70179a311b6856c2a00f7b8bfe | 2026-01-01T00:00:00-05:00 | MotivNet: Evolving Meta-Sapiens into an Emotionally Intelligent Foundation Model | arXiv:2512.24231v1 Announce Type: new Abstract: In this paper, we introduce MotivNet, a generalizable facial emotion recognition model for robust real-world application. Current state-of-the-art FER models tend to have weak generalization when tested on diverse data, leading to deteriorated performance in the real worl... | https://arxiv.org/abs/2512.24231 | Academic Papers | svg |
e7371f4b3287d14138e9d64077c5e5526f3f6da717a4592d7be91a2faa009403 | 2026-01-01T00:00:00-05:00 | SC-LDPC Codes Over $\mathbb{F}_q$: Minimum Distance, Decoding Analysis and Threshold Saturation | arXiv:2512.24232v1 Announce Type: new Abstract: We investigate random spatially coupled low-density parity-check (SC-LDPC) code ensembles over finite fields. Under different variable-node edge-spreading rules, the random Tanner graphs of several coupled ensembles are defined by multiple independent, uniformly random mo... | https://arxiv.org/abs/2512.24232 | Academic Papers | svg |
88e9b02c6ab517804ff3ef5534a7b7992a0ce361ccdd55e28d0aa91e166664a5 | 2026-01-01T00:00:00-05:00 | LAILA: A Large Trait-Based Dataset for Arabic Automated Essay Scoring | arXiv:2512.24235v1 Announce Type: new Abstract: Automated Essay Scoring (AES) has gained increasing attention in recent years, yet research on Arabic AES remains limited due to the lack of publicly available datasets. To address this, we introduce LAILA, the largest publicly available Arabic AES dataset to date, compri... | https://arxiv.org/abs/2512.24235 | Academic Papers | svg |
1f3d27a799868926f70c22cc3d82286c3e00d2c51324bcff7d75b71472d41b1f | 2026-01-01T00:00:00-05:00 | A Framing and Analysis of Applicative Tangible Interfaces | arXiv:2512.24237v1 Announce Type: new Abstract: The investigation of tangible user interfaces commenced approximately thirty years ago. Questions on its commercial potential become more pressing as the field becomes mature. To take the field one step further -- as the emergence of components contributed to the commerci... | https://arxiv.org/abs/2512.24237 | Academic Papers | svg |
94a2258ab389b4b3122bf8bbe6f165082487cd5ee9a71572c7fea3cce8ee0f02 | 2026-01-01T00:00:00-05:00 | Spatial Discretization for Fine-Grain Zone Checks with STARKs | arXiv:2512.24238v1 Announce Type: new Abstract: Many location-based services rely on a point-in-polygon test (PiP), checking whether a point or a trajectory lies inside a geographic zone. Since geometric operations are expensive in zero-knowledge proofs, privately performing the PiP test is challenging. In this paper, ... | https://arxiv.org/abs/2512.24238 | Academic Papers | svg |
a4dc178c0075b12d6dfc42a8abd624332e4fb4553040d859afcec4779c7245cd | 2026-01-01T00:00:00-05:00 | The Uncanny Valley in medical simulation-based training: a visual summary | arXiv:2512.24240v1 Announce Type: new Abstract: The purpose of this review article is to provide a bibliographical as well as evidence-based visual guide regarding the effect of ``Uncanny Valley'' (UV) and how it profoundly influences medical virtual reality simulation-based training. The phenomenon, where increasingly... | https://arxiv.org/abs/2512.24240 | Academic Papers | svg |
59c934c6987bc1a1bd8568e70d9171a88758281ab1ceb12cab1c2848c7feace9 | 2026-01-01T00:00:00-05:00 | MambaSeg: Harnessing Mamba for Accurate and Efficient Image-Event Semantic Segmentation | arXiv:2512.24243v1 Announce Type: new Abstract: Semantic segmentation is a fundamental task in computer vision with wide-ranging applications, including autonomous driving and robotics. While RGB-based methods have achieved strong performance with CNNs and Transformers, their effectiveness degrades under fast motion, l... | https://arxiv.org/abs/2512.24243 | Academic Papers | svg |
25e6973d43e129298553182fe687eefb7c357f2300b166549c964cb02b98307e | 2026-01-01T00:00:00-05:00 | Time-Aware Adaptive Side Information Fusion for Sequential Recommendation | arXiv:2512.24246v1 Announce Type: new Abstract: Incorporating item-side information, such as category and brand, into sequential recommendation is a well-established and effective approach for improving performance. However, despite significant advancements, current models are generally limited by three key challenges:... | https://arxiv.org/abs/2512.24246 | Academic Papers | svg |
2eaec33a4c17f3919fab2d18be6237d2c419f6c8ccfb91adf91350327b10f7d4 | 2026-01-01T00:00:00-05:00 | Heteroscedastic Bayesian Optimization-Based Dynamic PID Tuning for Accurate and Robust UAV Trajectory Tracking | arXiv:2512.24249v1 Announce Type: new Abstract: Unmanned Aerial Vehicles (UAVs) play an important role in various applications, where precise trajectory tracking is crucial. However, conventional control algorithms for trajectory tracking often exhibit limited performance due to the underactuated, nonlinear, and highly... | https://arxiv.org/abs/2512.24249 | Academic Papers | svg |
a1728efd3eb8bc6877cffe0197926e7e6e1a98075f551cc952673b2ee81d3d9d | 2026-01-01T00:00:00-05:00 | Deep Reinforcement Learning for Solving the Fleet Size and Mix Vehicle Routing Problem | arXiv:2512.24251v1 Announce Type: new Abstract: The Fleet Size and Mix Vehicle Routing Problem (FSMVRP) is a prominent variant of the Vehicle Routing Problem (VRP), extensively studied in operations research and computational science. FSMVRP requires simultaneous decisions on fleet composition and routing, making it hi... | https://arxiv.org/abs/2512.24251 | Academic Papers | svg |
0d0ada21ae6753c960da470fd5a4ee120ab9849f585fbb8243aceb46373c4210 | 2026-01-01T00:00:00-05:00 | Early Prediction of Sepsis using Heart Rate Signals and Genetic Optimized LSTM Algorithm | arXiv:2512.24253v1 Announce Type: new Abstract: Sepsis, characterized by a dysregulated immune response to infection, results in significant mortality, morbidity, and healthcare costs. The timely prediction of sepsis progression is crucial for reducing adverse outcomes through early intervention. Despite the developmen... | https://arxiv.org/abs/2512.24253 | Academic Papers | svg |
bb822144bc6099fefc58304363dad0a6610e6aed7be7c80ee24f0909721bab8b | 2026-01-01T00:00:00-05:00 | How Would Oblivious Memory Boost Graph Analytics on Trusted Processors? | arXiv:2512.24255v1 Announce Type: new Abstract: Trusted processors provide a way to perform joint computations while preserving data privacy. To overcome the performance degradation caused by data-oblivious algorithms to prevent information leakage, we explore the benefits of oblivious memory (OM) integrated in process... | https://arxiv.org/abs/2512.24255 | Academic Papers | svg |
8d182980bb2b2a3b93e48912a1f63a747a308bd65cec4445b6bb2bec580e8182 | 2026-01-01T00:00:00-05:00 | Tracing the Flow of Knowledge From Science to Technology Using Deep Learning | arXiv:2512.24259v1 Announce Type: new Abstract: We develop a language similarity model suitable for working with patents and scientific publications at the same time. In a horse race-style evaluation, we subject eight language (similarity) models to predict credible Patent-Paper Citations. We find that our Pat-SPECTER ... | https://arxiv.org/abs/2512.24259 | Academic Papers | svg |
f06312594ab90587435308a00a025841b5ed3fb727aa167f5b0b407d81530389 | 2026-01-01T00:00:00-05:00 | Physically-Grounded Manifold Projection with Foundation Priors for Metal Artifact Reduction in Dental CBCT | arXiv:2512.24260v1 Announce Type: new Abstract: Metal artifacts in Dental CBCT severely obscure anatomical structures, hindering diagnosis. Current deep learning for Metal Artifact Reduction (MAR) faces limitations: supervised methods suffer from spectral blurring due to "regression-to-the-mean", while unsupervised one... | https://arxiv.org/abs/2512.24260 | Academic Papers | svg |
e58a70f8da3d3dcb9867f22129af0ba882282f1cb27ea1c23c086e10ef673890 | 2026-01-01T00:00:00-05:00 | Constrained Language Model Policy Optimization via Risk-aware Stepwise Alignment | arXiv:2512.24263v1 Announce Type: new Abstract: When fine-tuning pre-trained Language Models (LMs) to exhibit desired behaviors, maintaining control over risk is critical for ensuring both safety and trustworthiness. Most existing safety alignment methods, such as Safe RLHF and SACPO, typically operate under a risk-neu... | https://arxiv.org/abs/2512.24263 | Academic Papers | svg |
7c82dfb6df1ad1c782b83be83ff847cc8b81722e0d738e97e4b985ffc5f5e31c | 2026-01-01T00:00:00-05:00 | Joint Selection for Large-Scale Pre-Training Data via Policy Gradient-based Mask Learning | arXiv:2512.24265v1 Announce Type: new Abstract: A fine-grained data recipe is crucial for pre-training large language models, as it can significantly enhance training efficiency and model performance. One important ingredient in the recipe is to select samples based on scores produced by defined rules, LLM judgment, or... | https://arxiv.org/abs/2512.24265 | Academic Papers | svg |
dd66b59434bdeeeab4e9b996da5a6e037ebc9758d7853cf98044202e724a1d9a | 2026-01-01T00:00:00-05:00 | RAGPart & RAGMask: Retrieval-Stage Defenses Against Corpus Poisoning in Retrieval-Augmented Generation | arXiv:2512.24268v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a promising paradigm to enhance large language models (LLMs) with external knowledge, reducing hallucinations and compensating for outdated information. However, recent studies have exposed a critical vulnerability in RA... | https://arxiv.org/abs/2512.24268 | Academic Papers | svg |
581134e28e6c2ad0714fd6868ce297ae8ff315899da80e91612233027834268c | 2026-01-01T00:00:00-05:00 | Taming Hallucinations: Boosting MLLMs' Video Understanding via Counterfactual Video Generation | arXiv:2512.24271v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have made remarkable progress in video understanding. However, they suffer from a critical vulnerability: an over-reliance on language priors, which can lead to visual ungrounded hallucinations, especially when processing counterfa... | https://arxiv.org/abs/2512.24271 | Academic Papers | svg |
fe0526ad12996da0949271c5b515d7d41efb11dd3363f79fcd22ce236a39f24f | 2026-01-01T00:00:00-05:00 | Local Path Optimization in The Latent Space Using Learned Distance Gradient | arXiv:2512.24272v1 Announce Type: new Abstract: Constrained motion planning is a common but challenging problem in robotic manipulation. In recent years, data-driven constrained motion planning algorithms have shown impressive planning speed and success rate. Among them, the latent motion method based on manifold appro... | https://arxiv.org/abs/2512.24272 | Academic Papers | svg |
6b8c4cc982dab43f8a34769245d49f80a2b490accbd976acb4a9c4ad7d6d96c3 | 2026-01-01T00:00:00-05:00 | LiftProj: Space Lifting and Projection-Based Panorama Stitching | arXiv:2512.24276v1 Announce Type: new Abstract: Traditional image stitching techniques have predominantly utilized two-dimensional homography transformations and mesh warping to achieve alignment on a planar surface. While effective for scenes that are approximately coplanar or exhibit minimal parallax, these approache... | https://arxiv.org/abs/2512.24276 | Academic Papers | svg |
561fd09033ee23a5264899b98e44047d7f1682f5b0ad323d5345092c0e82d6bd | 2026-01-01T00:00:00-05:00 | One-shot synthesis of rare gastrointestinal lesions improves diagnostic accuracy and clinical training | arXiv:2512.24278v1 Announce Type: new Abstract: Rare gastrointestinal lesions are infrequently encountered in routine endoscopy, restricting the data available for developing reliable artificial intelligence (AI) models and training novice clinicians. Here we present EndoRare, a one-shot, retraining-free generative fra... | https://arxiv.org/abs/2512.24278 | Academic Papers | svg |
59909ce23ca96e63d77123eab3c80614a3ba136d35e6a7e29a5081516dc495cd | 2026-01-01T00:00:00-05:00 | Safe Sliding Mode Control for Marine Vessels Using High-Order Control Barrier Functions and Fast Projection | arXiv:2512.24281v1 Announce Type: new Abstract: This paper presents a novel safe control framework that integrates Sliding Mode Control (SMC), High-Order Control Barrier Functions (HOCBFs) with state-dependent adaptiveness and a lightweight projection for collision-free navigation of an over-actuated 3-DOF marine surfa... | https://arxiv.org/abs/2512.24281 | Academic Papers | svg |
c5a5f81bbe128e9c150835e5d9aeab06725c7c95fc54643d275e6a7bc7d1d73f | 2026-01-01T00:00:00-05:00 | DRL-TH: Jointly Utilizing Temporal Graph Attention and Hierarchical Fusion for UGV Navigation in Crowded Environments | arXiv:2512.24284v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) methods have demonstrated potential for autonomous navigation and obstacle avoidance of unmanned ground vehicles (UGVs) in crowded environments. Most existing approaches rely on single-frame observation and employ simple concatenation for... | https://arxiv.org/abs/2512.24284 | Academic Papers | svg |
367eea0de7c1f56951f8ec521477962582b9386d39447cfdfa3d2744bfd62c4c | 2026-01-01T00:00:00-05:00 | Data Heterogeneity-Aware Client Selection for Federated Learning in Wireless Networks | arXiv:2512.24286v1 Announce Type: new Abstract: Federated Learning (FL) enables mobile edge devices, functioning as clients, to collaboratively train a decentralized model while ensuring local data privacy. However, the efficiency of FL in wireless networks is limited not only by constraints on communication and comput... | https://arxiv.org/abs/2512.24286 | Academic Papers | svg |
079ccfbbf2b7dd817b49f297f18fcfa970548cd5017c992642d2472c910466bd | 2026-01-01T00:00:00-05:00 | Real-world Reinforcement Learning from Suboptimal Interventions | arXiv:2512.24288v1 Announce Type: new Abstract: Real-world reinforcement learning (RL) offers a promising approach to training precise and dexterous robotic manipulation policies in an online manner, enabling robots to learn from their own experience while gradually reducing human labor. However, prior real-world RL me... | https://arxiv.org/abs/2512.24288 | Academic Papers | svg |
921211dfbd827f339502108afe2b34b0e115d67355ac361f9a1c75667fad58d8 | 2026-01-01T00:00:00-05:00 | Automated Analysis of Sustainability Reports: Using Large Language Models for the Extraction and Prediction of EU Taxonomy-Compliant KPIs | arXiv:2512.24289v1 Announce Type: new Abstract: The manual, resource-intensive process of complying with the EU Taxonomy presents a significant challenge for companies. While Large Language Models (LLMs) offer a path to automation, research is hindered by a lack of public benchmark datasets. To address this gap, we int... | https://arxiv.org/abs/2512.24289 | Academic Papers | svg |
2c01dfe9590aed11d7524d43b1ca851deacc425e0fc00edbaad63443361b71f0 | 2026-01-01T00:00:00-05:00 | Virtual-Eyes: Quantitative Validation of a Lung CT Quality-Control Pipeline for Foundation-Model Cancer Risk Prediction | arXiv:2512.24294v1 Announce Type: new Abstract: Robust preprocessing is rarely quantified in deep-learning pipelines for low-dose CT (LDCT) lung cancer screening. We develop and validate Virtual-Eyes, a clinically motivated 16-bit CT quality-control pipeline, and measure its differential impact on generalist foundation... | https://arxiv.org/abs/2512.24294 | Academic Papers | svg |
410ab1214269c891f95045d504e7d7c9b9b9b2e15309f9352e1e7b51962fb86b | 2026-01-01T00:00:00-05:00 | Figure It Out: Improving the Frontier of Reasoning with Active Visual Thinking | arXiv:2512.24297v1 Announce Type: new Abstract: Complex reasoning problems often involve implicit spatial, geometric, and structural relationships that are not explicitly encoded in text. While recent reasoning models have achieved strong performance across many domains, purely text-based reasoning struggles to represe... | https://arxiv.org/abs/2512.24297 | Academic Papers | svg |
9a84bf003cbdc320f94aa26f92fd4af937f1276f356e6c6ee329f16e8db51ae9 | 2026-01-01T00:00:00-05:00 | World In Your Hands: A Large-Scale and Open-source Ecosystem for Learning Human-centric Manipulation in the Wild | arXiv:2512.24310v1 Announce Type: new Abstract: Large-scale pre-training is fundamental for generalization in language and vision models, but data for dexterous hand manipulation remains limited in scale and diversity, hindering policy generalization. Limited scenario diversity, misaligned modalities, and insufficient ... | https://arxiv.org/abs/2512.24310 | Academic Papers | svg |
c9fd525a005467bd3b1a2a5cf121feea8d88ea19c045a68876533d7e23c06ca2 | 2026-01-01T00:00:00-05:00 | QianfanHuijin Technical Report: A Novel Multi-Stage Training Paradigm for Finance Industrial LLMs | arXiv:2512.24314v1 Announce Type: new Abstract: Domain-specific enhancement of Large Language Models (LLMs) within the financial context has long been a focal point of industrial application. While previous models such as BloombergGPT and Baichuan-Finance primarily focused on knowledge enhancement, the deepening comple... | https://arxiv.org/abs/2512.24314 | Academic Papers | svg |
1f4a1755518d8f103a76a0dead249c5d6a84c4f9813a64b792b4ff676c9ba863 | 2026-01-01T00:00:00-05:00 | UniAct: Unified Motion Generation and Action Streaming for Humanoid Robots | arXiv:2512.24321v1 Announce Type: new Abstract: A long-standing objective in humanoid robotics is the realization of versatile agents capable of following diverse multimodal instructions with human-level flexibility. Despite advances in humanoid control, bridging high-level multimodal perception with whole-body executi... | https://arxiv.org/abs/2512.24321 | Academic Papers | svg |
8e8e0ba6792e51dbed16839febdbc136be6d4147fabb23b933b1fb227c4e6a5a | 2026-01-01T00:00:00-05:00 | Robust Egocentric Referring Video Object Segmentation via Dual-Modal Causal Intervention | arXiv:2512.24323v1 Announce Type: new Abstract: Egocentric Referring Video Object Segmentation (Ego-RVOS) aims to segment the specific object actively involved in a human action, as described by a language query, within first-person videos. This task is critical for understanding egocentric human behavior. However, ach... | https://arxiv.org/abs/2512.24323 | Academic Papers | svg |
1e2614154d04040f26cc009b5ee169b1a9f6748a1f07d4e7a4352cf4eb782b06 | 2026-01-01T00:00:00-05:00 | Empower Low-Altitude Economy: A Reliability-Aware Dynamic Weighting Allocation for Multi-modal UAV Beam Prediction | arXiv:2512.24324v1 Announce Type: new Abstract: The low-altitude economy (LAE) is rapidly expanding driven by urban air mobility, logistics drones, and aerial sensing, while fast and accurate beam prediction in uncrewed aerial vehicles (UAVs) communications is crucial for achieving reliable connectivity. Current resear... | https://arxiv.org/abs/2512.24324 | Academic Papers | svg |
b9b9e2f6aa769f9d2ff21ba7dec176f236b6cccd2035c39134033488e8d76c0f | 2026-01-01T00:00:00-05:00 | MaRCA: Multi-Agent Reinforcement Learning for Dynamic Computation Allocation in Large-Scale Recommender Systems | arXiv:2512.24325v1 Announce Type: new Abstract: Modern recommender systems face significant computational challenges due to growing model complexity and traffic scale, making efficient computation allocation critical for maximizing business revenue. Existing approaches typically simplify multi-stage computation resourc... | https://arxiv.org/abs/2512.24325 | Academic Papers | svg |
2c72e461df2074b2ba5efa339de15b3043f70e4431b076628c9ed49d5a92bc45 | 2026-01-01T00:00:00-05:00 | 3D Path-Following Guidance via Nonlinear Model Predictive Control for Fixed-Wing Small UAS | arXiv:2512.24326v1 Announce Type: new Abstract: This paper presents the design, implementation, and flight test results of two novel 3D path-following guidance algorithms based on nonlinear model predictive control (MPC), with specific application to fixed-wing small uncrewed aircraft systems. To enable MPC, control-au... | https://arxiv.org/abs/2512.24326 | Academic Papers | svg |
d6af014364e50e3fe0d40b08337a3ff4fc2acb6ed3198cef0e3adad88836e6da | 2026-01-01T00:00:00-05:00 | World model inspired sarcasm reasoning with large language model agents | arXiv:2512.24329v1 Announce Type: new Abstract: Sarcasm understanding is a challenging problem in natural language processing, as it requires capturing the discrepancy between the surface meaning of an utterance and the speaker's intentions as well as the surrounding social context. Although recent advances in deep lea... | https://arxiv.org/abs/2512.24329 | Academic Papers | svg |
c5b7e2de439e86f71b7fc0403bee1e81792bce372fcb08dce2683d579a400670 | 2026-01-01T00:00:00-05:00 | SenseNova-MARS: Empowering Multimodal Agentic Reasoning and Search via Reinforcement Learning | arXiv:2512.24330v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) can solve complex tasks through agentic reasoning, their capabilities remain largely constrained to text-oriented chain-of-thought or isolated tool invocation. They fail to exhibit the human-like proficiency required to seamlessly inter... | https://arxiv.org/abs/2512.24330 | Academic Papers | svg |
d9f6e0083cdff560e2992891cfc498f8c1e4db84c4f55a6cd9610563e3858942 | 2026-01-01T00:00:00-05:00 | Spatial-aware Vision Language Model for Autonomous Driving | arXiv:2512.24331v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) show significant promise for end-to-end autonomous driving by leveraging the common sense embedded in language models, their reliance on 2D image cues for complex scene understanding and decision-making presents a critical bottleneck fo... | https://arxiv.org/abs/2512.24331 | Academic Papers | svg |
b4f1bde2851c52caa0fb4659e1b63a19e0ff7c02577c3e7eab7f95ca552e10b4 | 2026-01-01T00:00:00-05:00 | A density-based framework for community detection in attributed networks | arXiv:2512.24336v1 Announce Type: new Abstract: Community structure in social and collaborative networks often emerges from a complex interplay between structural mechanisms, such as degree heterogeneity and leader-driven attraction, and homophily on node attributes. Existing community detection methods typically focus... | https://arxiv.org/abs/2512.24336 | Academic Papers | svg |
546c1af2cb82de5bb18bbeec2db601d8acfc7b2a1ac2fb89fffaebdeaa66356a | 2026-01-01T00:00:00-05:00 | The Mechanics of CNN Filtering with Rectification | arXiv:2512.24338v1 Announce Type: new Abstract: This paper proposes elementary information mechanics as a new model for understanding the mechanical properties of convolutional filtering with rectification, inspired by physical theories of special relativity and quantum mechanics. We consider kernels decomposed into or... | https://arxiv.org/abs/2512.24338 | Academic Papers | svg |
06fa7485e50a9ed0a1c1fe16ae9b71114649f0a3f036e42a2610cfc9a722b14a | 2026-01-01T00:00:00-05:00 | Proof-Carrying PWL Verification for ReLU Networks: Convex-Hull Semantics, Exact \SMT/\MILP Encodings, and Symbolic Certificate Checking | arXiv:2512.24339v1 Announce Type: new Abstract: ReLU networks are piecewise-linear (PWL), enabling exact symbolic verification via \SMT(\LRA) or \MILP. However, safety claims in certification pipelines require not only correctness but also \emph{checkable evidence}. We develop a proof-carrying verification core for PWL... | https://arxiv.org/abs/2512.24339 | Academic Papers | svg |
b6ba9962e0d36314c2811dd82d9c7afb396ae92bbe38c07ed9bb55e4502bf55e | 2026-01-01T00:00:00-05:00 | DermaVQA-DAS: Dermatology Assessment Schema (DAS) & Datasets for Closed-Ended Question Answering & Segmentation in Patient-Generated Dermatology Images | arXiv:2512.24340v1 Announce Type: new Abstract: Recent advances in dermatological image analysis have been driven by large-scale annotated datasets; however, most existing benchmarks focus on dermatoscopic images and lack patient-authored queries and clinical context, limiting their applicability to patient-centered ca... | https://arxiv.org/abs/2512.24340 | Academic Papers | svg |
d37aa9e38b22231b59b9198225d4e3f53b126ae53e6593d4f23987a5d6b22b27 | 2026-01-01T00:00:00-05:00 | FedSecureFormer: A Fast, Federated and Secure Transformer Framework for Lightweight Intrusion Detection in Connected and Autonomous Vehicles | arXiv:2512.24345v1 Announce Type: new Abstract: This works presents an encoder-only transformer built with minimum layers for intrusion detection in the domain of Connected and Autonomous Vehicles using Federated Learning. | https://arxiv.org/abs/2512.24345 | Academic Papers | svg |
d8c81778a3ceb6f6609e1649894d93533a12d77334edbc7d79134b85cacaa60e | 2026-01-01T00:00:00-05:00 | Effects of Algorithmic Visibility on Conspiracy Communities: Reddit after Epstein's 'Suicide' | arXiv:2512.24351v1 Announce Type: new Abstract: This paper examines how algorithmic visibility shapes a large conspiracy community on Reddit after Jeffrey Epstein's death. We ask whether homepage exposure changes who join r/conspiracy, how long they stay, and how they adapt linguistically, compared with users who arriv... | https://arxiv.org/abs/2512.24351 | Academic Papers | svg |
2a8d2e1b9dfb322cdc82afef97c4c6d6f1c31867f15949c6cc1d70de88ccd613 | 2026-01-01T00:00:00-05:00 | Faster Algorithms for Global Minimum Vertex-Cut in Directed Graphs | arXiv:2512.24355v1 Announce Type: new Abstract: We study the directed global minimum vertex-cut problem: given a directed vertex-weighted graph $G$, compute a vertex-cut $(L,S,R)$ in $G$ of minimum value, which is defined to be the total weight of all vertices in $S$. The problem, together with its edge-based variant, ... | https://arxiv.org/abs/2512.24355 | Academic Papers | svg |
3109f244dcff19fa142504da411d111a0fb0d359bd4db51075455d7b93f70f9b | 2026-01-01T00:00:00-05:00 | Learning Context: A Unified Framework and Roadmap for Context-Aware AI in Education | arXiv:2512.24362v1 Announce Type: new Abstract: We introduce a unified Learning Context (LC) framework designed to transition AI-based education from context-blind mimicry to a principled, holistic understanding of the learner. This white paper provides a multidisciplinary roadmap for making teaching and learning syste... | https://arxiv.org/abs/2512.24362 | Academic Papers | svg |
0e042fa759d3b6e76071b70cad3382cc0a1007b22ca2411d100e6fe852d252ed | 2026-01-01T00:00:00-05:00 | On the Factual Consistency of Text-based Explainable Recommendation Models | arXiv:2512.24366v1 Announce Type: new Abstract: Text-based explainable recommendation aims to generate natural-language explanations that justify item recommendations, to improve user trust and system transparency. Although recent advances leverage LLMs to produce fluent outputs, a critical question remains underexplor... | https://arxiv.org/abs/2512.24366 | Academic Papers | svg |
1c41dfd2a38599709680edbe33ec01ea2c56a6ab1b82abef2e4e965c108a2bd2 | 2026-01-01T00:00:00-05:00 | Skim-Aware Contrastive Learning for Efficient Document Representation | arXiv:2512.24373v1 Announce Type: new Abstract: Although transformer-based models have shown strong performance in word- and sentence-level tasks, effectively representing long documents, especially in fields like law and medicine, remains difficult. Sparse attention mechanisms can handle longer inputs, but are resourc... | https://arxiv.org/abs/2512.24373 | Academic Papers | svg |
68380676ed60c0eef4aded376878101149ce57eab4b250fd89d5b6191a43cce9 | 2026-01-01T00:00:00-05:00 | New Insights into Cascaded Geometric Flight Control: From Performance Guarantees to Practical Pitfalls | arXiv:2512.24377v1 Announce Type: new Abstract: We present a new stability proof for cascaded geometric control used by aerial vehicles tracking time-varying position trajectories. Our approach uses sliding variables and a recently proposed quaternion-based sliding controller to demonstrate that exponentially convergen... | https://arxiv.org/abs/2512.24377 | Academic Papers | svg |
62490d74aa73c6735f8ef5aac713cf65336d702eb88426e3ce9f5eb4b9c0d9a8 | 2026-01-01T00:00:00-05:00 | Tubular Riemannian Laplace Approximations for Bayesian Neural Networks | arXiv:2512.24381v1 Announce Type: new Abstract: Laplace approximations are among the simplest and most practical methods for approximate Bayesian inference in neural networks, yet their Euclidean formulation struggles with the highly anisotropic, curved loss surfaces and large symmetry groups that characterize modern d... | https://arxiv.org/abs/2512.24381 | Academic Papers | svg |
3db583cba9413dd2c6087dc66f84ecbacbe95a691b4435970193cac26f6224d8 | 2026-01-01T00:00:00-05:00 | Geometric Multi-Session Map Merging with Learned Local Descriptors | arXiv:2512.24384v1 Announce Type: new Abstract: Multi-session map merging is crucial for extended autonomous operations in large-scale environments. In this paper, we present GMLD, a learning-based local descriptor framework for large-scale multi-session point cloud map merging that systematically aligns maps collected... | https://arxiv.org/abs/2512.24384 | Academic Papers | svg |
92dec7a2008adcc4e98d6da2e86143dfd9c35ceb3d8569a650e9232b1f44f923 | 2026-01-01T00:00:00-05:00 | Forging Spatial Intelligence: A Roadmap of Multi-Modal Data Pre-Training for Autonomous Systems | arXiv:2512.24385v1 Announce Type: new Abstract: The rapid advancement of autonomous systems, including self-driving vehicles and drones, has intensified the need to forge true Spatial Intelligence from multi-modal onboard sensor data. While foundation models excel in single-modal contexts, integrating their capabilitie... | https://arxiv.org/abs/2512.24385 | Academic Papers | svg |
63be561eeeafa1a6a7d8025b167836f684370fc55e0886c9d9b5c7b92aed656d | 2026-01-01T00:00:00-05:00 | RedunCut: Measurement-Driven Sampling and Accuracy Performance Modeling for Low-Cost Live Video Analytics | arXiv:2512.24386v1 Announce Type: new Abstract: Live video analytics (LVA) runs continuously across massive camera fleets, but inference cost with modern vision models remains high. To address this, dynamic model size selection (DMSS) is an attractive approach: it is content-aware but treats models as black boxes, and ... | https://arxiv.org/abs/2512.24386 | Academic Papers | svg |
d399eced34a27bfb5f7d380622bbe0ba89301dd00aa827adc91487c10f391d80 | 2026-01-01T00:00:00-05:00 | FAST-IDS: A Fast Two-Stage Intrusion Detection System with Hybrid Compression for Real-Time Threat Detection in Connected and Autonomous Vehicles | arXiv:2512.24391v1 Announce Type: new Abstract: We have implemented a multi-stage IDS for CAVs that can be deployed to resourec-constrained environments after hybrid model compression. | https://arxiv.org/abs/2512.24391 | Academic Papers | svg |
b08ee448928037bbe19707858af9375216cac1d295c69976ec0efff81b0d9ef3 | 2026-01-01T00:00:00-05:00 | SourceBroken: A large-scale analysis on the (un)reliability of SourceRank in the PyPI ecosystem | arXiv:2512.24400v1 Announce Type: new Abstract: SourceRank is a scoring system made of 18 metrics that assess the popularity and quality of open-source packages. Despite being used in several recent studies, none has thoroughly analyzed its reliability against evasion attacks aimed at inflating the score of malicious p... | https://arxiv.org/abs/2512.24400 | Academic Papers | svg |
64291c3d651888476754791ebf15f5e89a282441393c86b6cfed08443bfa84ca | 2026-01-01T00:00:00-05:00 | Fast and Realistic Automated Scenario Simulations and Reporting for an Autonomous Racing Stack | arXiv:2512.24402v1 Announce Type: new Abstract: In this paper, we describe the automated simulation and reporting pipeline implemented for our autonomous racing stack, ur.autopilot. The backbone of the simulation is based on a high-fidelity model of the vehicle interfaced as a Functional Mockup Unit (FMU). The pipeline... | https://arxiv.org/abs/2512.24402 | Academic Papers | svg |
6987bb7ce6d5f52b971936090027b70be4fb85cc579ac5c1b2e75ddb17c2513e | 2026-01-01T00:00:00-05:00 | Lifting Vision: Ground to Aerial Localization with Reasoning Guided Planning | arXiv:2512.24404v1 Announce Type: new Abstract: Multimodal intelligence development recently show strong progress in visual understanding and high level reasoning. Though, most reasoning system still reply on textual information as the main medium for inference. This limit their effectiveness in spatial tasks such as v... | https://arxiv.org/abs/2512.24404 | Academic Papers | svg |
d1ba2074445dd33be5555c59c736ccd577f7c7ef5e9fb05d181972a0776f5d8f | 2026-01-01T00:00:00-05:00 | Sufficient and Necessary Conditions for Eckart-Young-like Result for Tubal Tensors | arXiv:2512.24405v1 Announce Type: new Abstract: A valuable feature of the tubal tensor framework is that many familiar constructions from matrix algebra carry over to tensors, including SVD and notions of rank. Most importantly, it has been shown that for a specific family of tubal products, an Eckart-Young type theore... | https://arxiv.org/abs/2512.24405 | Academic Papers | svg |
89605785828c2c389cc8a99e46f348c35a66fe6d17b0093e5820bad467d2b98a | 2026-01-01T00:00:00-05:00 | Efficient Inference for Inverse Reinforcement Learning and Dynamic Discrete Choice Models | arXiv:2512.24407v1 Announce Type: new Abstract: Inverse reinforcement learning (IRL) and dynamic discrete choice (DDC) models explain sequential decision-making by recovering reward functions that rationalize observed behavior. Flexible IRL methods typically rely on machine learning but provide no guarantees for valid ... | https://arxiv.org/abs/2512.24407 | Academic Papers | svg |
a59a6ee39f031cf06b8aaef3159905643f6a0734b2576f8592587a910a420788 | 2026-01-01T00:00:00-05:00 | DyStream: Streaming Dyadic Talking Heads Generation via Flow Matching-based Autoregressive Model | arXiv:2512.24408v1 Announce Type: new Abstract: Generating realistic, dyadic talking head video requires ultra-low latency. Existing chunk-based methods require full non-causal context windows, introducing significant delays. This high latency critically prevents the immediate, non-verbal feedback required for a realis... | https://arxiv.org/abs/2512.24408 | Academic Papers | svg |
4572b4d5f62228b501b707a1dbbe5fff8a0c734c154f36f784aaced94bca96c2 | 2026-01-01T00:00:00-05:00 | Comparing Approaches to Automatic Summarization in Less-Resourced Languages | arXiv:2512.24410v1 Announce Type: new Abstract: Automatic text summarization has achieved high performance in high-resourced languages like English, but comparatively less attention has been given to summarization in less-resourced languages. This work compares a variety of different approaches to summarization from ze... | https://arxiv.org/abs/2512.24410 | Academic Papers | svg |
a2603719568b0e9f1a2fa4bb2219275be5a1fae7fabacac2449a670e0a03eb73 | 2026-01-01T00:00:00-05:00 | AI-Driven Evaluation of Surgical Skill via Action Recognition | arXiv:2512.24411v1 Announce Type: new Abstract: The development of effective training and evaluation strategies is critical. Conventional methods for assessing surgical proficiency typically rely on expert supervision, either through onsite observation or retrospective analysis of recorded procedures. However, these ap... | https://arxiv.org/abs/2512.24411 | Academic Papers | svg |
c3aa23eb9be43a4a78b7e40e288625aa904d75878f2cbe7ddea1533b6db9fc5c | 2026-01-01T00:00:00-05:00 | Language Model Agents Under Attack: A Cross Model-Benchmark of Profit-Seeking Behaviors in Customer Service | arXiv:2512.24415v1 Announce Type: new Abstract: Customer-service LLM agents increasingly make policy-bound decisions (refunds, rebooking, billing disputes), but the same ``helpful'' interaction style can be exploited: a small fraction of users can induce unauthorized concessions, shifting costs to others and eroding tr... | https://arxiv.org/abs/2512.24415 | Academic Papers | svg |
62d0e0919e8a5d0e6d8921b87a62f3c638c16d4feb8562edf30c035aabeadd4c | 2026-01-01T00:00:00-05:00 | GateChain: A Blockchain Based Application for Country Entry Exit Registry Management | arXiv:2512.24416v1 Announce Type: new Abstract: Recording entry and exit records for a country, with properties such as confidentiality, integrity, and auditability, is increasingly important due to rising international mobility and security requirements. Traditional border control systems, which rely on centralised da... | https://arxiv.org/abs/2512.24416 | Academic Papers | svg |
6aa8d6ab959decb333d603e40feef3e868e453e3d1036220a9a8e1f1ab119743 | 2026-01-01T00:00:00-05:00 | Counterfactual VLA: Self-Reflective Vision-Language-Action Model with Adaptive Reasoning | arXiv:2512.24426v1 Announce Type: new Abstract: Recent reasoning-augmented Vision-Language-Action (VLA) models have improved the interpretability of end-to-end autonomous driving by generating intermediate reasoning traces. Yet these models primarily describe what they perceive and intend to do, rarely questioning whet... | https://arxiv.org/abs/2512.24426 | Academic Papers | svg |
f486de5600d2228161a01370406e040cb9a9360ca5321f055ca11bf9d5746d7f | 2026-01-01T00:00:00-05:00 | Subsecond 3D Mesh Generation for Robot Manipulation | arXiv:2512.24428v1 Announce Type: new Abstract: 3D meshes are a fundamental representation widely used in computer science and engineering. In robotics, they are particularly valuable because they capture objects in a form that aligns directly with how robots interact with the physical world, enabling core capabilities... | https://arxiv.org/abs/2512.24428 | Academic Papers | svg |
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