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6881a28b86a9792d7f893af57ae650b3cbf86ff102cc1a7ba11c418e53bb5405 | 2026-01-01T00:00:00-05:00 | Hardware Acceleration for Neural Networks: A Comprehensive Survey | arXiv:2512.23914v1 Announce Type: new Abstract: Neural networks have become a dominant computational workload across cloud and edge platforms, but rapid growth in model size and deployment diversity has exposed hardware bottlenecks increasingly dominated by memory movement, communication, and irregular operators rather... | https://arxiv.org/abs/2512.23914 | Academic Papers | svg |
6c7b75b3143d132af392296a1dde42165892877ae2868a6d66794f985d0bbd4b | 2026-01-01T00:00:00-05:00 | In Memorium: The Academic Journal | arXiv:2512.23915v1 Announce Type: new Abstract: We reflect on the life and influence of the academic journal, charting their history and contributions, discussing how their influence changed society, and examining how in death they will be mourned for what they initially stood for but in the end had moved so far from t... | https://arxiv.org/abs/2512.23915 | Academic Papers | svg |
96ad2447ba2f560b0a6ea0ad5327fb50229e5542fe60a74e77517d27c346cf50 | 2026-01-01T00:00:00-05:00 | Constraint Breeds Generalization: Temporal Dynamics as an Inductive Bias | arXiv:2512.23916v1 Announce Type: new Abstract: Conventional deep learning prioritizes unconstrained optimization, yet biological systems operate under strict metabolic constraints. We propose that these physical constraints shape dynamics to function not as limitations, but as a temporal inductive bias that breeds gen... | https://arxiv.org/abs/2512.23916 | Academic Papers | svg |
7639e866de121a292386cbcce2ff1bd48ce74620c76deebfcdf50724d9f75ce3 | 2026-01-01T00:00:00-05:00 | Analysis of Collaboration in CS Prizewinning with a Nobel-Turing Comparison | arXiv:2512.23919v1 Announce Type: new Abstract: In the scientific community, prizes play a pivotal role in shaping research trajectories by conferring credibility and offering financial incentives to researchers. Yet, we know little about the relationship between academic collaborations and prizewinning. By analyzing o... | https://arxiv.org/abs/2512.23919 | Academic Papers | svg |
7005aadf503c6f19f93a4329574ab2d1f67bb14d081bf94420021fa0ab05765c | 2026-01-01T00:00:00-05:00 | Learning to learn skill assessment for fetal ultrasound scanning | arXiv:2512.23920v1 Announce Type: new Abstract: Traditionally, ultrasound skill assessment has relied on expert supervision and feedback, a process known for its subjectivity and time-intensive nature. Previous works on quantitative and automated skill assessment have predominantly employed supervised learning methods,... | https://arxiv.org/abs/2512.23920 | Academic Papers | svg |
ad6c35cb428508caf502b3acd8ee8ead0d5dbfb12bd8a40f9ba7217fd9b46d24 | 2026-01-01T00:00:00-05:00 | Interactive Machine Learning: From Theory to Scale | arXiv:2512.23924v1 Announce Type: new Abstract: Machine learning has achieved remarkable success across a wide range of applications, yet many of its most effective methods rely on access to large amounts of labeled data or extensive online interaction. In practice, acquiring high-quality labels and making decisions th... | https://arxiv.org/abs/2512.23924 | Academic Papers | svg |
f661784024f2b775b0705fd725838c38bdc32a4f157da57217a7daa74b25a5ef | 2026-01-01T00:00:00-05:00 | Hojabr: Towards a Theory of Everything for AI and Data Analytics | arXiv:2512.23925v1 Announce Type: new Abstract: Modern data analytics pipelines increasingly combine relational queries, graph processing, and tensor computation within a single application, but existing systems remain fragmented across paradigms, execution models, and research communities. This fragmentation results i... | https://arxiv.org/abs/2512.23925 | Academic Papers | svg |
e9fbd1c4b0ded3bd84fce8c8dfdb982c4036f6e595cba22adebb30f64aad2b35 | 2026-01-01T00:00:00-05:00 | Identification of fixations and saccades in eye-tracking data using adaptive threshold-based method | arXiv:2512.23926v1 Announce Type: new Abstract: Properties of ocular fixations and saccades are highly stochastic during many experimental tasks, and their statistics are often used as proxies for various aspects of cognition. Although distinguishing saccades from fixations is not trivial, experimentalists generally us... | https://arxiv.org/abs/2512.23926 | Academic Papers | svg |
b2e35aceddbd3d90796c522d8d3a85850d186a59ef265e68973b1253e249167c | 2026-01-01T00:00:00-05:00 | SRM at 30: Lessons from Early Data-Centric Networking and Their Impact on Named Data Networking | arXiv:2512.23928v1 Announce Type: new Abstract: A 1995 SIGCOMM paper, "A Reliable Multicast Framework for Light-weight Sessions and Application-Level Framing", commonly known as SRM, explored a fundamentally new approach to reliable multiparty data delivery. Rather than adapting established sender-driven reliable unica... | https://arxiv.org/abs/2512.23928 | Academic Papers | svg |
593d7e0212a9c514e033d29de5b967e2ff1ed45bef1198746ddac2f2089600a3 | 2026-01-01T00:00:00-05:00 | A Proof-of-Concept for Explainable Disease Diagnosis Using Large Language Models and Answer Set Programming | arXiv:2512.23932v1 Announce Type: new Abstract: Accurate disease prediction is vital for timely intervention, effective treatment, and reducing medical complications. While symbolic AI has been applied in healthcare, its adoption remains limited due to the effort required for constructing high-quality knowledge bases. ... | https://arxiv.org/abs/2512.23932 | Academic Papers | svg |
7780d4ee3f1b13b79a1c2d5087e96ca4b3b922b2de0e0803629695ca15be2321 | 2026-01-01T00:00:00-05:00 | MGML: A Plug-and-Play Meta-Guided Multi-Modal Learning Framework for Incomplete Multimodal Brain Tumor Segmentation | arXiv:2512.23936v1 Announce Type: new Abstract: Leveraging multimodal information from Magnetic Resonance Imaging (MRI) plays a vital role in lesion segmentation, especially for brain tumors. However, in clinical practice, multimodal MRI data are often incomplete, making it challenging to fully utilize the available in... | https://arxiv.org/abs/2512.23936 | Academic Papers | svg |
6cb63f16aa8c9d09f32f880126bbba031e3386166e35bb5194da38f7ff859e8c | 2026-01-01T00:00:00-05:00 | Learnable Query Aggregation with KV Routing for Cross-view Geo-localisation | arXiv:2512.23938v1 Announce Type: new Abstract: Cross-view geo-localisation (CVGL) aims to estimate the geographic location of a query image by matching it with images from a large-scale database. However, the significant view-point discrepancies present considerable challenges for effective feature aggregation and ali... | https://arxiv.org/abs/2512.23938 | Academic Papers | svg |
22779fcd18672ca125c947dbe77cf41dd77c0e88d6c06735522366ebca3e4e1f | 2026-01-01T00:00:00-05:00 | Disentangling Learning from Judgment: Representation Learning for Open Response Analytics | arXiv:2512.23941v1 Announce Type: new Abstract: Open-ended responses are central to learning, yet automated scoring often conflates what students wrote with how teachers grade. We present an analytics-first framework that separates content signals from rater tendencies, making judgments visible and auditable via analyt... | https://arxiv.org/abs/2512.23941 | Academic Papers | svg |
070d6ca31cae05c3c783ee92a87d0adf7db6652184c7be24efd496f3f198ef5d | 2026-01-01T00:00:00-05:00 | Kinematic-Based Assessment of Surgical Actions in Microanastomosis | arXiv:2512.23942v1 Announce Type: new Abstract: Proficiency in microanastomosis is a critical surgical skill in neurosurgery, where the ability to precisely manipulate fine instruments is crucial to successful outcomes. These procedures require sustained attention, coordinated hand movements, and highly refined motor s... | https://arxiv.org/abs/2512.23942 | Academic Papers | svg |
ef09207f05ea36d400d2d8e56046bfa3fe791c458ebfb67e43ab3a9a60419321 | 2026-01-01T00:00:00-05:00 | Statistical Guarantees in the Search for Less Discriminatory Algorithms | arXiv:2512.23943v1 Announce Type: new Abstract: Recent scholarship has argued that firms building data-driven decision systems in high-stakes domains like employment, credit, and housing should search for "less discriminatory algorithms" (LDAs) (Black et al., 2024). That is, for a given decision problem, firms consider... | https://arxiv.org/abs/2512.23943 | Academic Papers | svg |
672bcc6504b6ea23bcba5d682efeaceab3c08aa0c76881d3abd846771b165d47 | 2026-01-01T00:00:00-05:00 | Decoupling Constraint from Two Direction in Evolutionary Constrained Multi-objective Optimization | arXiv:2512.23945v1 Announce Type: new Abstract: Real-world Constrained Multi-objective Optimization Problems (CMOPs) often contain multiple constraints, and understanding and utilizing the coupling between these constraints is crucial for solving CMOPs. However, existing Constrained Multi-objective Evolutionary Algorit... | https://arxiv.org/abs/2512.23945 | Academic Papers | svg |
2536fbb08a24aeed8f3a25fd7e4cadb74d9cafb5d7b5743efe2196cb7ada6310 | 2026-01-01T00:00:00-05:00 | Improved Balanced Classification with Theoretically Grounded Loss Functions | arXiv:2512.23947v1 Announce Type: new Abstract: The balanced loss is a widely adopted objective for multi-class classification under class imbalance. By assigning equal importance to all classes, regardless of their frequency, it promotes fairness and ensures that minority classes are not overlooked. However, directly ... | https://arxiv.org/abs/2512.23947 | Academic Papers | svg |
f6ba6579e705c54ac0cee87bd78fe5221b0898b944ef23310e61a3845aa955a2 | 2026-01-01T00:00:00-05:00 | DivQAT: Enhancing Robustness of Quantized Convolutional Neural Networks against Model Extraction Attacks | arXiv:2512.23948v1 Announce Type: new Abstract: Convolutional Neural Networks (CNNs) and their quantized counterparts are vulnerable to extraction attacks, posing a significant threat of IP theft. Yet, the robustness of quantized models against these attacks is little studied compared to large models. Previous defenses... | https://arxiv.org/abs/2512.23948 | Academic Papers | svg |
4a06271ed2c5f7787e806dbe821e96b791eb05751899b1bbffdb1bce09326d50 | 2026-01-01T00:00:00-05:00 | U-Net-Like Spiking Neural Networks for Single Image Dehazing | arXiv:2512.23950v1 Announce Type: new Abstract: Image dehazing is a critical challenge in computer vision, essential for enhancing image clarity in hazy conditions. Traditional methods often rely on atmospheric scattering models, while recent deep learning techniques, specifically Convolutional Neural Networks (CNNs) a... | https://arxiv.org/abs/2512.23950 | Academic Papers | svg |
20118a8e087277cde98559a1b91282bd78a83f42157d220f2cf3e6d820620e75 | 2026-01-01T00:00:00-05:00 | Squeezing Edge Performance: A Sensitivity-Aware Container Management for Heterogeneous Tasks | arXiv:2512.23952v1 Announce Type: new Abstract: Edge computing enables latency-critical applications to process data close to end devices, yet task heterogeneity and limited resources pose significant challenges to efficient orchestration. This paper presents a measurement-driven, container-based resource management fr... | https://arxiv.org/abs/2512.23952 | Academic Papers | svg |
096ae0fbd15bffac72e7c7153f0c784533c2b18e417e7c38c786a0a38d0ce7bb | 2026-01-01T00:00:00-05:00 | T2VAttack: Adversarial Attack on Text-to-Video Diffusion Models | arXiv:2512.23953v1 Announce Type: new Abstract: The rapid evolution of Text-to-Video (T2V) diffusion models has driven remarkable advancements in generating high-quality, temporally coherent videos from natural language descriptions. Despite these achievements, their vulnerability to adversarial attacks remains largely... | https://arxiv.org/abs/2512.23953 | Academic Papers | svg |
e07bd9d5bd5b42668ccd636e3fd7bdce2a9401ddeaf63a328e14434a88104a82 | 2026-01-01T00:00:00-05:00 | Improving Multi-step RAG with Hypergraph-based Memory for Long-Context Complex Relational Modeling | arXiv:2512.23959v1 Announce Type: new Abstract: Multi-step retrieval-augmented generation (RAG) has become a widely adopted strategy for enhancing large language models (LLMs) on tasks that demand global comprehension and intensive reasoning. Many RAG systems incorporate a working memory module to consolidate retrieved... | https://arxiv.org/abs/2512.23959 | Academic Papers | svg |
d9d0029f7433ad74a592ebc63469c0dc6a5c04d13ed1b827d4dd22219a5769be | 2026-01-01T00:00:00-05:00 | An Comparative Analysis about KYC on a Recommendation System Toward Agentic Recommendation System | arXiv:2512.23961v1 Announce Type: new Abstract: This research presents a cutting-edge recommendation system utilizing agentic AI for KYC (Know Your Customer in the financial domain), and its evaluation across five distinct content verticals: Advertising (Ad), News, Gossip, Sharing (User-Generated Content), and Technolo... | https://arxiv.org/abs/2512.23961 | Academic Papers | svg |
a6cb5df48bdaa7599c1e4d9e62d5ca238c8e8cee6024f3feb1a69f59457181ce | 2026-01-01T00:00:00-05:00 | Physics-informed Graph Neural Networks for Operational Flood Modeling | arXiv:2512.23964v1 Announce Type: new Abstract: Flood models inform strategic disaster management by simulating the spatiotemporal hydrodynamics of flooding. While physics-based numerical flood models are accurate, their substantial computational cost limits their use in operational settings where rapid predictions are... | https://arxiv.org/abs/2512.23964 | Academic Papers | svg |
e4a723626c5496852c58f1d4b704784ff85b58a819797292cb6825b2473333c6 | 2026-01-01T00:00:00-05:00 | Multimodal sampling via Schr\"odinger-F\"ollmer samplers with temperatures | arXiv:2512.23965v1 Announce Type: new Abstract: Generating samples from complex and high-dimensional distributions is ubiquitous in various scientific fields of statistical physics, Bayesian inference, scientific computing and machine learning. Very recently, Huang et al. (IEEE Trans. Inform. Theory, 2025) proposed new... | https://arxiv.org/abs/2512.23965 | Academic Papers | svg |
5bd41cee720358d41444e4db9537a773b6d45572e0242e2501a5e3b30af789eb | 2026-01-01T00:00:00-05:00 | Efficient Context Scaling with LongCat ZigZag Attention | arXiv:2512.23966v1 Announce Type: new Abstract: We introduce LongCat ZigZag Attention (LoZA), which is a sparse attention scheme designed to transform any existing full-attention models into sparse versions with rather limited compute budget. In long-context scenarios, LoZA can achieve significant speed-ups both for pr... | https://arxiv.org/abs/2512.23966 | Academic Papers | svg |
d358e82e70c902b09d54ad35ddefb49977eb3828e8d5bbfab08c9003bfceb7fc | 2026-01-01T00:00:00-05:00 | HERO-Sign: Hierarchical Tuning and Efficient Compiler-Time GPU Optimizations for SPHINCS+ Signature Generation | arXiv:2512.23969v1 Announce Type: new Abstract: SPHINCS+ is a stateless hash-based signature scheme that provides strong post quantum security, but its signature generation is slow due to intensive hash computations. GPUs offer massive parallelism that can potentially accelerate SPHINCS+ signatures. However, existing G... | https://arxiv.org/abs/2512.23969 | Academic Papers | svg |
7a4a038aa8788b60baf4ac1c1655bf3d3eb455549b685ff84713239404e1fcd7 | 2026-01-01T00:00:00-05:00 | CEC-Zero: Zero-Supervision Character Error Correction with Self-Generated Rewards | arXiv:2512.23971v1 Announce Type: new Abstract: Large-scale Chinese spelling correction (CSC) remains critical for real-world text processing, yet existing LLMs and supervised methods lack robustness to novel errors and rely on costly annotations. We introduce CEC-Zero, a zero-supervision reinforcement learning framewo... | https://arxiv.org/abs/2512.23971 | Academic Papers | svg |
75ba99b7961d24e48235ff701842792c1956a071015accd0bb568df3d33833f1 | 2026-01-01T00:00:00-05:00 | SHIELD: Spherical-Projection Hybrid-Frontier Integration for Efficient LiDAR-based Drone Exploration | arXiv:2512.23972v1 Announce Type: new Abstract: This paper introduces SHIELD, a Spherical-Projection Hybrid-Frontier Integration for Efficient LiDAR-based Drone exploration method. Although laser LiDAR offers the advantage of a wide field of view, its application in UAV exploration still faces several challenges. The o... | https://arxiv.org/abs/2512.23972 | Academic Papers | svg |
5b30dda2b8a8d3085e4be8e010b6f1d27fc43edf191deb51dcdb59531ab785ba | 2026-01-01T00:00:00-05:00 | A Community-Aware Framework for Influence Maximization with Explicit Accounting for Inter-Community Influence | arXiv:2512.23973v1 Announce Type: new Abstract: Influence Maximization (IM) seeks to identify a small set of seed nodes in a social network to maximize expected information spread under a diffusion model. While community-based approaches improve scalability by exploiting modular structure, they typically assume indepen... | https://arxiv.org/abs/2512.23973 | Academic Papers | svg |
a805cc53fa71298576008d6565257448ebe26b3ef2f34ac8f121c1bdbf4b57f8 | 2026-01-01T00:00:00-05:00 | Exploring the Potential of Spiking Neural Networks in UWB Channel Estimation | arXiv:2512.23975v1 Announce Type: new Abstract: Although existing deep learning-based Ultra-Wide Band (UWB) channel estimation methods achieve high accuracy, their computational intensity clashes sharply with the resource constraints of low-cost edge devices. Motivated by this, this letter explores the potential of Spi... | https://arxiv.org/abs/2512.23975 | Academic Papers | svg |
a83e47346674b4987a8ceca3a2c911a3cb4ff28a23eaa35d2c5a089d593e34c1 | 2026-01-01T00:00:00-05:00 | Causify DataFlow: A Framework For High-performance Machine Learning Stream Computing | arXiv:2512.23977v1 Announce Type: new Abstract: We present DataFlow, a computational framework for building, testing, and deploying high-performance machine learning systems on unbounded time-series data. Traditional data science workflows assume finite datasets and require substantial reimplementation when moving from... | https://arxiv.org/abs/2512.23977 | Academic Papers | svg |
37eb2929764f11e069e8e54ce35eb980a393694528c88a3e3d384e5abad0235d | 2026-01-01T00:00:00-05:00 | Assured Autonomy: How Operations Research Powers and Orchestrates Generative AI Systems | arXiv:2512.23978v1 Announce Type: new Abstract: Generative artificial intelligence (GenAI) is shifting from conversational assistants toward agentic systems -- autonomous decision-making systems that sense, decide, and act within operational workflows. This shift creates an autonomy paradox: as GenAI systems are grante... | https://arxiv.org/abs/2512.23978 | Academic Papers | svg |
6d3b21f7ea27d3380999b72ddec4e3afec4ebc7d5238769106f01d0bdd1e8f06 | 2026-01-01T00:00:00-05:00 | Information-Theoretic Quality Metric of Low-Dimensional Embeddings | arXiv:2512.23981v1 Announce Type: new Abstract: In this work we study the quality of low-dimensional embeddings from an explicitly information-theoretic perspective. We begin by noting that classical evaluation metrics such as stress, rank-based neighborhood criteria, or Local Procrustes quantify distortions in distanc... | https://arxiv.org/abs/2512.23981 | Academic Papers | svg |
33f87985a1821ec55b98283843e8634a92eb1af96ca36ea4667d2abea111dc7c | 2026-01-01T00:00:00-05:00 | Coding With AI: From a Reflection on Industrial Practices to Future Computer Science and Software Engineering Education | arXiv:2512.23982v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have introduced new paradigms in software development, including vibe coding, AI-assisted coding, and agentic coding, fundamentally reshaping how software is designed, implemented, and maintained. Prior research has primaril... | https://arxiv.org/abs/2512.23982 | Academic Papers | svg |
53232505890b549e1cfccccb8623ad41af406b4e196627fbfe10a3af968c2975 | 2026-01-01T00:00:00-05:00 | DriveExplorer: Images-Only Decoupled 4D Reconstruction with Progressive Restoration for Driving View Extrapolation | arXiv:2512.23983v1 Announce Type: new Abstract: This paper presents an effective solution for view extrapolation in autonomous driving scenarios. Recent approaches focus on generating shifted novel view images from given viewpoints using diffusion models. However, these methods heavily rely on priors such as LiDAR poin... | https://arxiv.org/abs/2512.23983 | Academic Papers | svg |
25ec2a4d1d5e06531961cccd96d69c319f42b98c136d57974bff74725c7d0877 | 2026-01-01T00:00:00-05:00 | Anomaly detection in satellite imagery through temporal inpainting | arXiv:2512.23986v1 Announce Type: new Abstract: Detecting surface changes from satellite imagery is critical for rapid disaster response and environmental monitoring, yet remains challenging due to the complex interplay between atmospheric noise, seasonal variations, and sensor artifacts. Here we show that deep learnin... | https://arxiv.org/abs/2512.23986 | Academic Papers | svg |
b3325381495a0c5bbf062a10286e4db53626ebc49f9d2d15208b9fa3b97b0c4a | 2026-01-01T00:00:00-05:00 | MeLeMaD: Adaptive Malware Detection via Chunk-wise Feature Selection and Meta-Learning | arXiv:2512.23987v1 Announce Type: new Abstract: Confronting the substantial challenges of malware detection in cybersecurity necessitates solutions that are both robust and adaptable to the ever-evolving threat environment. The paper introduces Meta Learning Malware Detection (MeLeMaD), a novel framework leveraging the... | https://arxiv.org/abs/2512.23987 | Academic Papers | svg |
93f31c948cd26eecfb4564aeecc3becd5b36642d4cc2a6eaa43eea10dcc44da3 | 2026-01-01T00:00:00-05:00 | Fantastic Reasoning Behaviors and Where to Find Them: Unsupervised Discovery of the Reasoning Process | arXiv:2512.23988v1 Announce Type: new Abstract: Despite the growing reasoning capabilities of recent large language models (LLMs), their internal mechanisms during the reasoning process remain underexplored. Prior approaches often rely on human-defined concepts (e.g., overthinking, reflection) at the word level to anal... | https://arxiv.org/abs/2512.23988 | Academic Papers | svg |
a6d96f03c8079c4b7c528dcce4490f645aa47de5475d3004846c6f62291bbe2e | 2026-01-01T00:00:00-05:00 | Bisplit graphs -- A Structural and algorithmic study | arXiv:2512.23989v1 Announce Type: new Abstract: A dominating set $S$ of a graph $G(V,E)$ is called a \textit{secure dominating set} if each vertex $u \in V(G) \setminus S$ is adjacent to a vertex $v \in S$ such that $(S \setminus \{v\}) \cup \{u\}$ is a dominating set of $G$. The \textit{secure domination number} $\gam... | https://arxiv.org/abs/2512.23989 | Academic Papers | svg |
fdd38af90369118ee9ea232ff7fb61d64c3bb0d3b07bc17a807d096ca4343b2f | 2026-01-01T00:00:00-05:00 | GCA-ResUNet: Medical Image Segmentation Using Grouped Coordinate Attention | arXiv:2512.23990v1 Announce Type: new Abstract: Accurate segmentation of heterogeneous anatomical structures is pivotal for computer-aided diagnosis and subsequent clinical decision-making. Although U-Net based convolutional neural networks have achieved remarkable progress, their intrinsic locality and largely homogen... | https://arxiv.org/abs/2512.23990 | Academic Papers | svg |
4bdf9fa852fa0a50b73fbe94e8655430345874b5c5a18a60a1d2b1deccc5166b | 2026-01-01T00:00:00-05:00 | PhyAVBench: A Challenging Audio Physics-Sensitivity Benchmark for Physically Grounded Text-to-Audio-Video Generation | arXiv:2512.23994v1 Announce Type: new Abstract: Text-to-audio-video (T2AV) generation underpins a wide range of applications demanding realistic audio-visual content, including virtual reality, world modeling, gaming, and filmmaking. However, existing T2AV models remain incapable of generating physically plausible soun... | https://arxiv.org/abs/2512.23994 | Academic Papers | svg |
7508c49bb42296bebfef8d5aa94e60e41bad5ad6256b516b726700627ef1681d | 2026-01-01T00:00:00-05:00 | RepetitionCurse: Measuring and Understanding Router Imbalance in Mixture-of-Experts LLMs under DoS Stress | arXiv:2512.23995v1 Announce Type: new Abstract: Mixture-of-Experts architectures have become the standard for scaling large language models due to their superior parameter efficiency. To accommodate the growing number of experts in practice, modern inference systems commonly adopt expert parallelism to distribute exper... | https://arxiv.org/abs/2512.23995 | Academic Papers | svg |
13f60183dc8e7cd0076e823d145fee3efeb5c610e411a9fb7b22cdcd27a6afd1 | 2026-01-01T00:00:00-05:00 | State Space Estimation for DPOR-based Model Checkers | arXiv:2512.23996v1 Announce Type: new Abstract: We study the estimation problem for concurrent programs: given a bounded program $P$, estimate the number of Mazurkiewicz trace-equivalence classes induced by its interleavings. This quantity informs two practical questions for enumeration-based model checking: how long a... | https://arxiv.org/abs/2512.23996 | Academic Papers | svg |
93bf7f4080ef7495b504c505f4071d9e228a468b272fb93f6ac0eb0e1ee4a313 | 2026-01-01T00:00:00-05:00 | Bridging Structure and Appearance: Topological Features for Robust Self-Supervised Segmentation | arXiv:2512.23997v1 Announce Type: new Abstract: Self-supervised semantic segmentation methods often fail when faced with appearance ambiguities. We argue that this is due to an over-reliance on unstable, appearance-based features such as shadows, glare, and local textures. We propose \textbf{GASeg}, a novel framework t... | https://arxiv.org/abs/2512.23997 | Academic Papers | svg |
4608fd859904a92cdfdc98b68b56dd6b95e446ab3689e310a6eba248a4228558 | 2026-01-01T00:00:00-05:00 | Improved 3D Gaussian Splatting of Unknown Spacecraft Structure Using Space Environment Illumination Knowledge | arXiv:2512.23998v1 Announce Type: new Abstract: This work presents a novel pipeline to recover the 3D structure of an unknown target spacecraft from a sequence of images captured during Rendezvous and Proximity Operations (RPO) in space. The target's geometry and appearance are represented as a 3D Gaussian Splatting (3... | https://arxiv.org/abs/2512.23998 | Academic Papers | svg |
065321126053f23c87eb2dd0de942cd5f20c94c6679d95abca11af812e6b5f43 | 2026-01-01T00:00:00-05:00 | WISE: Web Information Satire and Fakeness Evaluation | arXiv:2512.24000v1 Announce Type: new Abstract: Distinguishing fake or untrue news from satire or humor poses a unique challenge due to their overlapping linguistic features and divergent intent. This study develops WISE (Web Information Satire and Fakeness Evaluation) framework which benchmarks eight lightweight trans... | https://arxiv.org/abs/2512.24000 | Academic Papers | svg |
48d77e27c7d7d0dfe24ec6b65b52977b29def82dc000b2f8f7aa61714c17af7c | 2026-01-01T00:00:00-05:00 | Tracing the Heart's Pathways: ECG Representation Learning from a Cardiac Conduction Perspective | arXiv:2512.24002v1 Announce Type: new Abstract: The multi-lead electrocardiogram (ECG) stands as a cornerstone of cardiac diagnosis. Recent strides in electrocardiogram self-supervised learning (eSSL) have brightened prospects for enhancing representation learning without relying on high-quality annotations. Yet earlie... | https://arxiv.org/abs/2512.24002 | Academic Papers | svg |
e2e7959d444cfe14bbcc525dcaa1865e76c3d7660f25b5b5a0883efbc3d8909b | 2026-01-01T00:00:00-05:00 | TESO Tabu Enhanced Simulation Optimization for Noisy Black Box Problems | arXiv:2512.24007v1 Announce Type: new Abstract: Simulation optimization (SO) is frequently challenged by noisy evaluations, high computational costs, and complex, multimodal search landscapes. This paper introduces Tabu-Enhanced Simulation Optimization (TESO), a novel metaheuristic framework integrating adaptive search... | https://arxiv.org/abs/2512.24007 | Academic Papers | svg |
5031e4ca896e0f6fe7e314d7902fa6e1be39e687deeb3033f696ef03422b063f | 2026-01-01T00:00:00-05:00 | SPARK: Search Personalization via Agent-Driven Retrieval and Knowledge-sharing | arXiv:2512.24008v1 Announce Type: new Abstract: Personalized search demands the ability to model users' evolving, multi-dimensional information needs; a challenge for systems constrained by static profiles or monolithic retrieval pipelines. We present SPARK (Search Personalization via Agent-Driven Retrieval and Knowled... | https://arxiv.org/abs/2512.24008 | Academic Papers | svg |
7cabc69e33899ffa6113344b6a64c993ef2453cb0ce05e5e558a7c5be7ec6b29 | 2026-01-01T00:00:00-05:00 | Bridging the Perception-Cognition Gap:Re-engineering SAM2 with Hilbert-Mamba for Robust VLM-based Medical Diagnosis | arXiv:2512.24013v1 Announce Type: new Abstract: Recent studies suggest that Visual Language Models (VLMs) hold great potential for tasks such as automated medical diagnosis. However, processing complex three-dimensional (3D) multimodal medical images poses significant challenges - specifically, the effective integratio... | https://arxiv.org/abs/2512.24013 | Academic Papers | svg |
72a469dc7ba2e095f4549aaa090d83f198a43a659d856ce3959416e661509541 | 2026-01-01T00:00:00-05:00 | iCLP: Large Language Model Reasoning with Implicit Cognition Latent Planning | arXiv:2512.24014v1 Announce Type: new Abstract: Large language models (LLMs), when guided by explicit textual plans, can perform reliable step-by-step reasoning during problem-solving. However, generating accurate and effective textual plans remains challenging due to LLM hallucinations and the high diversity of task-s... | https://arxiv.org/abs/2512.24014 | Academic Papers | svg |
1503d41b6072cdfd11c99dd172e3713aca736f393c401578c2cc58dfe01d2005 | 2026-01-01T00:00:00-05:00 | On Exact Editing of Flow-Based Diffusion Models | arXiv:2512.24015v1 Announce Type: new Abstract: Recent methods in flow-based diffusion editing have enabled direct transformations between source and target image distribution without explicit inversion. However, the latent trajectories in these methods often exhibit accumulated velocity errors, leading to semantic inc... | https://arxiv.org/abs/2512.24015 | Academic Papers | svg |
0f163e047fd4b59e486bab26e6f41379d3952bbdf8062fccbfaeed47edc79825 | 2026-01-01T00:00:00-05:00 | FitControler: Toward Fit-Aware Virtual Try-On | arXiv:2512.24016v1 Announce Type: new Abstract: Realistic virtual try-on (VTON) concerns not only faithful rendering of garment details but also coordination of the style. Prior art typically pursues the former, but neglects a key factor that shapes the holistic style -- garment fit. Garment fit delineates how a garmen... | https://arxiv.org/abs/2512.24016 | Academic Papers | svg |
798b4de3030ce181f454c11777eb3a50246f2f5ac631c17034f86f2b30b6a8bc | 2026-01-01T00:00:00-05:00 | Structure-Guided Allocation of 2D Gaussians for Image Representation and Compression | arXiv:2512.24018v1 Announce Type: new Abstract: Recent advances in 2D Gaussian Splatting (2DGS) have demonstrated its potential as a compact image representation with millisecond-level decoding. However, existing 2DGS-based pipelines allocate representation capacity and parameter precision largely oblivious to image st... | https://arxiv.org/abs/2512.24018 | Academic Papers | svg |
09b498e2ad4ff6762e0be2e6fe216b4d44f12d19e08a1ffd0e19af5f3a640df8 | 2026-01-01T00:00:00-05:00 | FUSE-RSVLM: Feature Fusion Vision-Language Model for Remote Sensing | arXiv:2512.24022v1 Announce Type: new Abstract: Large vision-language models (VLMs) exhibit strong performance across various tasks. However, these VLMs encounter significant challenges when applied to the remote sensing domain due to the inherent differences between remote sensing images and natural images. Existing r... | https://arxiv.org/abs/2512.24022 | Academic Papers | svg |
e27aea8b3a32452ba832f222ae540b23364e386537e1b3ab50399f1b402363a7 | 2026-01-01T00:00:00-05:00 | RSAgent: Learning to Reason and Act for Text-Guided Segmentation via Multi-Turn Tool Invocations | arXiv:2512.24023v1 Announce Type: new Abstract: Text-guided object segmentation requires both cross-modal reasoning and pixel grounding abilities. Most recent methods treat text-guided segmentation as one-shot grounding, where the model predicts pixel prompts in a single forward pass to drive an external segmentor, whi... | https://arxiv.org/abs/2512.24023 | Academic Papers | svg |
11e677569df3b1d203cad3bf8d51eca1db5c8f74cec13bf546c8e6d175956464 | 2026-01-01T00:00:00-05:00 | PipeFlow: Pipelined Processing and Motion-Aware Frame Selection for Long-Form Video Editing | arXiv:2512.24026v1 Announce Type: new Abstract: Long-form video editing poses unique challenges due to the exponential increase in the computational cost from joint editing and Denoising Diffusion Implicit Models (DDIM) inversion across extended sequences. To address these limitations, we propose PipeFlow, a scalable, ... | https://arxiv.org/abs/2512.24026 | Academic Papers | svg |
e95737840dd82f05fbdbbd36aee2347659bf2682e786a425e741772876863757 | 2026-01-01T00:00:00-05:00 | Evaluation of Impression Difference of a Domestic Mobile Manipulator with Autonomous and/or Remote Control in Fetch-and-Carry Tasks | arXiv:2512.24029v1 Announce Type: new Abstract: A single service robot can present two distinct agencies: its onboard autonomy and an operator-mediated agency, yet users experience them through one physical body. We formalize this dual-agency structure as a User-Robot-Operator triad in an autonomous remote-control sett... | https://arxiv.org/abs/2512.24029 | Academic Papers | svg |
ed7e6a04d64dc4b6c52ccd9ee73c7312e0ac3d0199f799f540f8edaf67e1b154 | 2026-01-01T00:00:00-05:00 | Reinforced Diffusion: Learning to Push the Limits of Anisotropic Diffusion for Image Denoising | arXiv:2512.24035v1 Announce Type: new Abstract: Image denoising is an important problem in low-level vision and serves as a critical module for many image recovery tasks. Anisotropic diffusion is a wide family of image denoising approaches with promising performance. However, traditional anisotropic diffusion approache... | https://arxiv.org/abs/2512.24035 | Academic Papers | svg |
c3ebb59ea38734fecfadd5a84bc53f75f49bedcff594d4a150a70425db4067e0 | 2026-01-01T00:00:00-05:00 | Kidney Exchange: Faster Parameterized Algorithms and Tighter Lower Bounds | arXiv:2512.24037v1 Announce Type: new Abstract: The kidney exchange mechanism allows many patient-donor pairs who are otherwise incompatible with each other to come together and exchange kidneys along a cycle. However, due to infrastructure and legal constraints, kidney exchange can only be performed in small cycles in... | https://arxiv.org/abs/2512.24037 | Academic Papers | svg |
f0dd05a390709fba36affa5057605505f62403d736e6c7ee0efc1b793ae9915a | 2026-01-01T00:00:00-05:00 | A precise proof of the n-variable Bekic principle | arXiv:2512.24038v1 Announce Type: new Abstract: We provide a proof of the $n$-ary Beki\v{c} principle, which states that a vectorial fixpoint of size $n$ can be written in terms of nested fixpoints in each coordinate according to lexicographic order. The proof is inductive. | https://arxiv.org/abs/2512.24038 | Academic Papers | svg |
ef4c0ad425b45f83f8e72252f2e717360aaf3eb7b6edff3b43407dcf10e6efa3 | 2026-01-01T00:00:00-05:00 | Continuous Angular Power Spectrum Recovery From Channel Covariance via Chebyshev Polynomials | arXiv:2512.24039v1 Announce Type: new Abstract: This paper proposes a Chebyshev polynomial expansion framework for the recovery of a continuous angular power spectrum (APS) from channel covariance. By exploiting the orthogonality of Chebyshev polynomials in a transformed domain, we derive an exact series representation... | https://arxiv.org/abs/2512.24039 | Academic Papers | svg |
c84c19b0f2bc2814df733b9610127b9a3b21a18b37bd63ad8ad1c1fa78d91a05 | 2026-01-01T00:00:00-05:00 | ROAD: Reflective Optimization via Automated Debugging for Zero-Shot Agent Alignment | arXiv:2512.24040v1 Announce Type: new Abstract: Automatic Prompt Optimization (APO) has emerged as a critical technique for enhancing Large Language Model (LLM) performance, yet current state-of-the-art methods typically rely on large, labeled gold-standard development sets to compute fitness scores for evolutionary or... | https://arxiv.org/abs/2512.24040 | Academic Papers | svg |
b91e1e191259797f8b70f247856e94d08820be6b380cd8f3601c5fc39b317cad | 2026-01-01T00:00:00-05:00 | Jailbreaking Attacks vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race? | arXiv:2512.24044v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed, ensuring their safe use is paramount. Jailbreaking, adversarial prompts that bypass model alignment to trigger harmful outputs, present significant risks, with existing studies reporting high success rates in evad... | https://arxiv.org/abs/2512.24044 | Academic Papers | svg |
8169b6e0eaf11942261894fed23d9d33d07415d48b4129fb4c13ec5dc81c084b | 2026-01-01T00:00:00-05:00 | Beyond Dedicated-Active: A General Reliability Provisioning Framework for SFC Placement in Fog Computing | arXiv:2512.24049v1 Announce Type: new Abstract: The explosive growth of Internet of Things (IoT) devices has strained traditional cloud infrastructures, highlighting the need for low-latency and energy-efficient alternatives. Fog computing addresses this by placing computation near the network edge. However, limited an... | https://arxiv.org/abs/2512.24049 | Academic Papers | svg |
4771fbd18b36ded6f80aadcf0c09c91b4efecede2880c8343691b025851ec7d2 | 2026-01-01T00:00:00-05:00 | AHA: Aligning Large Audio-Language Models for Reasoning Hallucinations via Counterfactual Hard Negatives | arXiv:2512.24052v1 Announce Type: new Abstract: Although Large Audio-Language Models (LALMs) deliver state-of-the-art (SOTA) performance, they frequently suffer from hallucinations, e.g. generating text not grounded in the audio input. We analyze these grounding failures and identify a distinct taxonomy: Event Omission... | https://arxiv.org/abs/2512.24052 | Academic Papers | svg |
008110278d4656ba2390c7ff9769164fa8e182c9befaae59daa9cc4fe5361f59 | 2026-01-01T00:00:00-05:00 | Beyond Hallucinations: A Composite Score for Measuring Reliability in Open-Source Large Language Models | arXiv:2512.24058v1 Announce Type: new Abstract: Large Language Models (LLMs) like LLaMA, Mistral, and Gemma are increasingly used in decision-critical domains such as healthcare, law, and finance, yet their reliability remains uncertain. They often make overconfident errors, degrade under input shifts, and lack clear u... | https://arxiv.org/abs/2512.24058 | Academic Papers | svg |
6ea42402cdf77e47d2823bfd0f16177f278b8e4b396559bd4be998739ef4c132 | 2026-01-01T00:00:00-05:00 | Hyperspherical Graph Representation Learning via Adaptive Neighbor-Mean Alignment and Uniformity | arXiv:2512.24062v1 Announce Type: new Abstract: Graph representation learning (GRL) aims to encode structural and semantic dependencies of graph-structured data into low-dimensional embeddings. However, existing GRL methods often rely on surrogate contrastive objectives or mutual information maximization, which typical... | https://arxiv.org/abs/2512.24062 | Academic Papers | svg |
a73936f22c666a2a21cf2acebfe7698ac34f29bcf4aa7cf006cc7fd2a69708fa | 2026-01-01T00:00:00-05:00 | How and Why LLMs Generalize: A Fine-Grained Analysis of LLM Reasoning from Cognitive Behaviors to Low-Level Patterns | arXiv:2512.24063v1 Announce Type: new Abstract: Large Language Models (LLMs) display strikingly different generalization behaviors: supervised fine-tuning (SFT) often narrows capability, whereas reinforcement-learning (RL) tuning tends to preserve it. The reasons behind this divergence remain unclear, as prior studies ... | https://arxiv.org/abs/2512.24063 | Academic Papers | svg |
8ca9d1c6079f47ea860c8b4ae8e7770dd3e0f29bcf7007641d6a72179e468ec2 | 2026-01-01T00:00:00-05:00 | Neighbor-aware Instance Refining with Noisy Labels for Cross-Modal Retrieval | arXiv:2512.24064v1 Announce Type: new Abstract: In recent years, Cross-Modal Retrieval (CMR) has made significant progress in the field of multi-modal analysis. However, since it is time-consuming and labor-intensive to collect large-scale and well-annotated data, the annotation of multi-modal data inevitably contains ... | https://arxiv.org/abs/2512.24064 | Academic Papers | svg |
125586687a466392a3a89a81bbcd147e45fe8d9fe33604af1ca32af6a7837c82 | 2026-01-01T00:00:00-05:00 | Pathology Context Recalibration Network for Ocular Disease Recognition | arXiv:2512.24066v1 Announce Type: new Abstract: Pathology context and expert experience play significant roles in clinical ocular disease diagnosis. Although deep neural networks (DNNs) have good ocular disease recognition results, they often ignore exploring the clinical pathology context and expert experience priors ... | https://arxiv.org/abs/2512.24066 | Academic Papers | svg |
b6df2d348554ab5cbc441ae2cdcc9732850197337ed7c96b857593fa5697be56 | 2026-01-01T00:00:00-05:00 | Time-varying Mixing Matrix Design for Energy-efficient Decentralized Federated Learning | arXiv:2512.24069v1 Announce Type: new Abstract: We consider the design of mixing matrices to minimize the operation cost for decentralized federated learning (DFL) in wireless networks, with focus on minimizing the maximum per-node energy consumption. As a critical hyperparameter for DFL, the mixing matrix controls bot... | https://arxiv.org/abs/2512.24069 | Academic Papers | svg |
0c2032e8dd8579c75c8595d4be9427793396769edf57832b046a4bb48f959d8a | 2026-01-01T00:00:00-05:00 | CPePC: Cooperative and Predictive Popularity based Caching for Named Data Networks | arXiv:2512.24073v1 Announce Type: new Abstract: Caching content is an inherent feature of Named Data Networks. Limited cache capacity of routers warrants that the choice of content being cached is judiciously done. Existing techniques resort to caching popular content to maximize utilization. However, these methods exp... | https://arxiv.org/abs/2512.24073 | Academic Papers | svg |
10d62053a9fecb190669bb2d005d1af3cdfba792c14e46e951532910aa8bc2c6 | 2026-01-01T00:00:00-05:00 | Balanced Hierarchical Contrastive Learning with Decoupled Queries for Fine-grained Object Detection in Remote Sensing Images | arXiv:2512.24074v1 Announce Type: new Abstract: Fine-grained remote sensing datasets often use hierarchical label structures to differentiate objects in a coarse-to-fine manner, with each object annotated across multiple levels. However, embedding this semantic hierarchy into the representation learning space to improv... | https://arxiv.org/abs/2512.24074 | Academic Papers | svg |
7d210d0e6832974b747168e5a51333339c13534ca793f73aaee3c96dfe73868c | 2026-01-01T00:00:00-05:00 | Multi-Scenario Highway Lane-Change Intention Prediction: A Temporal Physics-Informed Multi-Modal Framework | arXiv:2512.24075v1 Announce Type: new Abstract: Lane-change intention prediction is safety-critical for autonomous driving and ADAS, but remains difficult in naturalistic traffic due to noisy kinematics, severe class imbalance, and limited generalization across heterogeneous highway scenarios. We propose Temporal Physi... | https://arxiv.org/abs/2512.24075 | Academic Papers | svg |
8c937591bc38a15d31f602c5e2cc3cc08cd5aefe1553f4ddfe482e49d9f99387 | 2026-01-01T00:00:00-05:00 | LoongFlow: Directed Evolutionary Search via a Cognitive Plan-Execute-Summarize Paradigm | arXiv:2512.24077v1 Announce Type: new Abstract: The transition from static Large Language Models (LLMs) to self-improving agents is hindered by the lack of structured reasoning in traditional evolutionary approaches. Existing methods often struggle with premature convergence and inefficient exploration in high-dimensio... | https://arxiv.org/abs/2512.24077 | Academic Papers | svg |
5fc309512528e3ffb419758a34a791bb00e30f734e282a775e6b767f8790ad52 | 2026-01-01T00:00:00-05:00 | High-dimensional Regret Minimization | arXiv:2512.24078v1 Announce Type: new Abstract: Multi-criteria decision making in large databases is very important in real world applications. Recently, an interactive query has been studied extensively in the database literature with the advantage of both the top-k query (with limited output size) and the skyline que... | https://arxiv.org/abs/2512.24078 | Academic Papers | svg |
2e750541d74f78eb3f148e2e533386773fe22644d2e49f9b78f5afe4da13ab60 | 2026-01-01T00:00:00-05:00 | RainFusion2.0: Temporal-Spatial Awareness and Hardware-Efficient Block-wise Sparse Attention | arXiv:2512.24086v1 Announce Type: new Abstract: In video and image generation tasks, Diffusion Transformer (DiT) models incur extremely high computational costs due to attention mechanisms, which limits their practical applications. Furthermore, with hardware advancements, a wide range of devices besides graphics proce... | https://arxiv.org/abs/2512.24086 | Academic Papers | svg |
58d618f2019857e3478603977a4e076955da25e31d871778dfd04334320c043d | 2026-01-01T00:00:00-05:00 | Random Multiplexing | arXiv:2512.24087v1 Announce Type: new Abstract: As wireless communication applications evolve from traditional multipath environments to high-mobility scenarios like unmanned aerial vehicles, multiplexing techniques have advanced accordingly. Traditional single-carrier frequency-domain equalization (SC-FDE) and orthogo... | https://arxiv.org/abs/2512.24087 | Academic Papers | svg |
6181e13c3b15daefed4ccf427f02d1566e0afef8301094f377eb549b7241556e | 2026-01-01T00:00:00-05:00 | FedLiTeCAN : A Federated Lightweight Transformer for Fast and Robust CAN Bus Intrusion Detection | arXiv:2512.24088v1 Announce Type: new Abstract: This work implements a lightweight Transformer model for IDS in the domain of Connected and Autonomous Vehicles | https://arxiv.org/abs/2512.24088 | Academic Papers | svg |
6bea20e889271a8646d1b75871ff3c8a2bbd465619a0db1525be27a5e2156e26 | 2026-01-01T00:00:00-05:00 | HY-MT1.5 Technical Report | arXiv:2512.24092v1 Announce Type: new Abstract: In this report, we introduce our latest translation models, HY-MT1.5-1.8B and HY-MT1.5-7B, a new family of machine translation models developed through a holistic training framework tailored for high-performance translation. Our methodology orchestrates a multi-stage pipe... | https://arxiv.org/abs/2512.24092 | Academic Papers | svg |
f9fcfc7204744306352faf050368e592c938c08f284748391961f6bf940ed15f | 2026-01-01T00:00:00-05:00 | Factorized Learning for Temporally Grounded Video-Language Models | arXiv:2512.24097v1 Announce Type: new Abstract: Recent video-language models have shown great potential for video understanding, but still struggle with accurate temporal grounding for event-level perception. We observe that two main factors in video understanding (i.e., temporal grounding and textual response) form a ... | https://arxiv.org/abs/2512.24097 | Academic Papers | svg |
72a8c6d94361c8fbefb39f637f7c355c996e4ce600391b46b85c9cae96932cf6 | 2026-01-01T00:00:00-05:00 | Training a Huggingface Model on AWS Sagemaker (Without Tears) | arXiv:2512.24098v1 Announce Type: new Abstract: The development of Large Language Models (LLMs) has primarily been driven by resource-rich research groups and industry partners. Due to the lack of on-premise computing resources required for increasingly complex models, many researchers are turning to cloud services lik... | https://arxiv.org/abs/2512.24098 | Academic Papers | svg |
65588fb502a576cf9032b8f36e39c52e6ada565f7edd87c6344b0e9f38d897d9 | 2026-01-01T00:00:00-05:00 | Think Before You Move: Latent Motion Reasoning for Text-to-Motion Generation | arXiv:2512.24100v1 Announce Type: new Abstract: Current state-of-the-art paradigms predominantly treat Text-to-Motion (T2M) generation as a direct translation problem, mapping symbolic language directly to continuous poses. While effective for simple actions, this System 1 approach faces a fundamental theoretical bottl... | https://arxiv.org/abs/2512.24100 | Academic Papers | svg |
a1218059b0221305b42a7f26166dae18d15e72f0b62dbc73a3c35ecd631ac3aa | 2026-01-01T00:00:00-05:00 | Economic and Technical Feasibility of V2G in Non-Road Mobile Machinery sector | arXiv:2512.24101v1 Announce Type: new Abstract: This paper investigates the economic and technical feasibility of integrating Vehicle-to-Grid (V2G) technology in the Non-Road Mobile Machinery (NRMM) sector. These often-idling assets, with their substantial battery capacities, present a unique opportunity to participate... | https://arxiv.org/abs/2512.24101 | Academic Papers | svg |
a7ce60e2c16683e9c499d50ddeb1fa06268c402dd353dfbf1efceec83b889d53 | 2026-01-01T00:00:00-05:00 | Autoregressivity in the Latent Space of a GP-VAE Language Model: An Empirical Ablation Study | arXiv:2512.24102v1 Announce Type: new Abstract: This paper provides an ablation-based analysis of latent autoregression in GP-VAE models, building upon our previous work introducing the architecture. Language models typically rely on an autoregressive factorization over tokens. In contrast, our prior work proposed shif... | https://arxiv.org/abs/2512.24102 | Academic Papers | svg |
6402d6f68c0c189030e109a9f8ce751a06afc0854dddca32fe6db473632ba38c | 2026-01-01T00:00:00-05:00 | Enhancing LLM Planning Capabilities through Intrinsic Self-Critique | arXiv:2512.24103v1 Announce Type: new Abstract: We demonstrate an approach for LLMs to critique their \emph{own} answers with the goal of enhancing their performance that leads to significant improvements over established planning benchmarks. Despite the findings of earlier research that has cast doubt on the effective... | https://arxiv.org/abs/2512.24103 | Academic Papers | svg |
19007e8c90618bba68f48ff626b85e157f81ab629f9aefadae436ee96ca44198 | 2026-01-01T00:00:00-05:00 | Multilevel Fair Allocation | arXiv:2512.24105v1 Announce Type: new Abstract: We introduce the concept of multilevel fair allocation of resources with tree-structured hierarchical relations among agents. While at each level it is possible to consider the problem locally as an allocation of an agent to its children, the multilevel allocation can be ... | https://arxiv.org/abs/2512.24105 | Academic Papers | svg |
4cb5329ab9c2464fe973d9183de26df44cbe77b7f9db3071728503050327059a | 2026-01-01T00:00:00-05:00 | When Wires Can't Keep Up: Reconfigurable AI Data Centers Empowered by Terahertz Wireless Communications | arXiv:2512.24110v1 Announce Type: new Abstract: The explosive growth of artificial intelligence (AI) workloads in modern data centers demands a radical transformation of interconnect architectures. Traditional copper and optical wiring face fundamental challenges in latency, power consumption, and rigidity, constrainin... | https://arxiv.org/abs/2512.24110 | Academic Papers | svg |
278c33b7e684f3955386dc81ee824c28f8658787b2e4d3a405a0784b68b1ddc0 | 2026-01-01T00:00:00-05:00 | Guided Diffusion-based Generation of Adversarial Objects for Real-World Monocular Depth Estimation Attacks | arXiv:2512.24111v1 Announce Type: new Abstract: Monocular Depth Estimation (MDE) serves as a core perception module in autonomous driving systems, but it remains highly susceptible to adversarial attacks. Errors in depth estimation may propagate through downstream decision making and influence overall traffic safety. E... | https://arxiv.org/abs/2512.24111 | Academic Papers | svg |
e0f6518362c1781bd41cfad4a90b794c29116a240f48965e6c4645b6f8921ff8 | 2026-01-01T00:00:00-05:00 | RflyUT-Sim: A Simulation Platform for Development and Testing of Complex Low-Altitude Traffic Control | arXiv:2512.24112v1 Announce Type: new Abstract: Significant challenges are posed by simulation and testing in the field of low-altitude unmanned aerial vehicle (UAV) traffic due to the high costs associated with large-scale UAV testing and the complexity of establishing low-altitude traffic test scenarios. Stringent sa... | https://arxiv.org/abs/2512.24112 | Academic Papers | svg |
fa3ae4be4bfa1789be94870b185afa2a8c67ec8bd9c1cc73ad12345487e09a8f | 2026-01-01T00:00:00-05:00 | CogRec: A Cognitive Recommender Agent Fusing Large Language Models and Soar for Explainable Recommendation | arXiv:2512.24113v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated a remarkable capacity in understanding user preferences for recommendation systems. However, they are constrained by several critical challenges, including their inherent "Black-Box" characteristics, susceptibility to knowled... | https://arxiv.org/abs/2512.24113 | Academic Papers | svg |
5959b101e120d91e8529d92b0711887ce34b10162d0cb049d439c75afd05588c | 2026-01-01T00:00:00-05:00 | GeoBench: Rethinking Multimodal Geometric Problem-Solving via Hierarchical Evaluation | arXiv:2512.24119v1 Announce Type: new Abstract: Geometric problem solving constitutes a critical branch of mathematical reasoning, requiring precise analysis of shapes and spatial relationships. Current evaluations of geometric reasoning in vision-language models (VLMs) face limitations, including the risk of test data... | https://arxiv.org/abs/2512.24119 | Academic Papers | svg |
fd0df44309aaddbc07e06a94effc36918549c2b18ba21bd8a94e0dfc7497b544 | 2026-01-01T00:00:00-05:00 | Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design | arXiv:2512.24120v1 Announce Type: new Abstract: Automated neural network architecture design remains a significant challenge in computer vision. Task diversity and computational constraints require both effective architectures and efficient search methods. Large Language Models (LLMs) present a promising alternative to... | https://arxiv.org/abs/2512.24120 | Academic Papers | svg |
1a9e215192ef81c683246417fdb6fb0f4bbb91657910fe17ee45ce2a9e1c43f9 | 2026-01-01T00:00:00-05:00 | High order numerical discretizations of the Einstein-Euler equations in the Generalized Harmonic formulation | arXiv:2512.24121v1 Announce Type: new Abstract: We propose two new alternative numerical schemes to solve the coupled Einstein-Euler equations in the Generalized Harmonic formulation. The first one is a finite difference (FD) Central Weighted Essentially Non-Oscillatory (CWENO) scheme on a traditional Cartesian mesh, w... | https://arxiv.org/abs/2512.24121 | Academic Papers | svg |
6c2a8597c9afe75c1584e206d93c42ad31b96664cd9f4fafc7787ff9885c74a7 | 2026-01-01T00:00:00-05:00 | OptRot: Mitigating Weight Outliers via Data-Free Rotations for Post-Training Quantization | arXiv:2512.24124v1 Announce Type: new Abstract: The presence of outliers in Large Language Models (LLMs) weights and activations makes them difficult to quantize. Recent work has leveraged rotations to mitigate these outliers. In this work, we propose methods that learn fusible rotations by minimizing principled and ch... | https://arxiv.org/abs/2512.24124 | Academic Papers | svg |
730aad133a532c093ff9ef6c6adbee6ac34a87e7cb6609335cc6f02f1c9e927a | 2026-01-01T00:00:00-05:00 | Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training | arXiv:2512.24125v1 Announce Type: new Abstract: General-purpose robotic systems operating in open-world environments must achieve both broad generalization and high-precision action execution, a combination that remains challenging for existing Vision-Language-Action (VLA) models. While large Vision-Language Models (VL... | https://arxiv.org/abs/2512.24125 | Academic Papers | svg |
d5f49d7dece2920866c4685175b8a9292ba1f6bebf5fab211d074543d4ae9246 | 2026-01-01T00:00:00-05:00 | Structure-preserving schemes for nonlinear symmetric hyperbolic and thermodynamically compatible systems of partial differential equations | arXiv:2512.24127v1 Announce Type: new Abstract: This paper aims at developing exactly energy-conservative and structure-preserving finite volume schemes for the discretisation of first-order symmetric-hyperbolic and thermodynamically compatible (SHTC) systems of partial differential equations in continuum physics. Due ... | https://arxiv.org/abs/2512.24127 | Academic Papers | svg |
ed73bfc7ae6dad41486f373d4a504928ca079ea932c0c189f3fde35d036859bc | 2026-01-01T00:00:00-05:00 | ROBOPOL: Social Robotics Meets Vehicular Communications for Cooperative Automated Driving | arXiv:2512.24129v1 Announce Type: new Abstract: On the way towards full autonomy, sharing roads between automated vehicles and human actors in so-called mixed traffic is unavoidable. Moreover, even if all vehicles on the road were autonomous, pedestrians would still be crossing the streets. We propose social robots as ... | https://arxiv.org/abs/2512.24129 | Academic Papers | svg |
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