๐ Original Info Title: ArXiv ID: 2512.18314 Date: Authors: Unknown ๐ Abstract Figure 1 . MatSpray Overview we utilize 2D material world knowlegde from 2D diffusion models to reconstruct 3D relightable objects. Given multi-view images of a target โฆ
๐ Original Info Title: ArXiv ID: 2512.18265 Date: Authors: Unknown ๐ Abstract Manufacturing planners face complex operational challenges that require seamless collaboration between human expertise and intelligent systems to achieve optimal โฆ
๐ Original Info Title: ArXiv ID: 2512.19959 Date: Authors: Unknown ๐ Abstract Mesh simplification is the process of reducing the number of vertices, edges and triangles in a three-dimensional (3D) mesh while preserving the overall shape and salient โฆ
๐ Original Info Title: ArXiv ID: 2512.18199 Date: Authors: Unknown ๐ Abstract Modern intrusion detection systems (IDS) leverage graph neural networks (GNNs) to detect malicious activity in system provenance data, but their decisions often remain a โฆ
๐ Original Info Title: ArXiv ID: 2512.19912 Date: Authors: Unknown ๐ Abstract In this work, we extend and generalize our solving strategy, first introduced in [1], based on a greedy optimization algorithm and the alternating direction method (ADM) โฆ
๐ Original Info Title: ArXiv ID: 2512.18561 Date: Authors: Unknown ๐ Abstract Large-scale networked multi-agent systems increasingly underpin critical infrastructure, yet their collective behavior can drift toward undesirable emergent norms that โฆ
๐ Original Info Title: ArXiv ID: 2512.18573 Date: Authors: Unknown ๐ Abstract Placenta Accreta Spectrum (PAS) is a serious obstetric condition that can be challenging to diagnose with Magnetic Resonance Imaging (MRI) due to variability in โฆ
๐ Original Info Title: ArXiv ID: 2512.19849 Date: Authors: Unknown ๐ Abstract Mixture-of-Experts (MoE) workloads rely on expert parallelism (EP) to achieve high GPU efficiency. State-of-the-art EP communication systems such as DeepEP demonstrate โฆ
๐ Original Info Title: ArXiv ID: 2512.19717 Date: Authors: Unknown ๐ Abstract Finding rare but useful solutions in very large candidate spaces is a recurring practical challenge across language generation, planning, and reinforcement learning. We โฆ
๐ Original Info Title: ArXiv ID: 2512.18189 Date: Authors: Unknown ๐ Abstract Cognitive computing models offer a formal and interpretable way to characterize human's deliberation and decisionmaking, yet their development remains labor-intensive. In โฆ
๐ Original Info Title: ArXiv ID: 2512.18412 Date: Authors: Unknown ๐ Abstract We propose a structural-graph approach to classifying contour images in a few-shot regime without using backpropagation. The core idea is to make structure the carrier of โฆ
๐ Original Info Title: ArXiv ID: 2512.19678 Date: Authors: Unknown ๐ Abstract Starting Image 1 st Frame 200 th Frame 3DGS Reconstruction * Corresponding author. warping historical content into novel views, this cache acts as a structural scaffold, โฆ
๐ Original Info Title: ArXiv ID: 2512.18603 Date: Authors: Unknown ๐ Abstract Locally covariant algebraic quantum field theory (LCQFT) satisfies Einstein causality through microcausality and operational no-signalling, yet Bell-type correlations โฆ
๐ Original Info Title: ArXiv ID: 2512.18040 Date: Authors: Unknown ๐ Abstract Why do physicists almost universally take the direction of positive rotation to be counterclockwise, and three-dimensional coordinates to be right-handed? This paper traces โฆ
๐ Original Info Title: ArXiv ID: 2512.19799 Date: Authors: Unknown ๐ Abstract Advances in AI have produced agents whose knowledge and operational capabilities are comparable to those of human scientists, revealing their potential to assist, โฆ
๐ Original Info Title: ArXiv ID: 2512.18735 Date: Authors: Unknown ๐ Abstract What's the state of the drawers beside the bed in two states? A. closed in both states ร B. closed first and open later โ C. open in both states D. open first and closed โฆ
๐ Original Info Title: ArXiv ID: 2512.18002 Date: Authors: Unknown ๐ Abstract For a century, quantum theory has posed a fundamental challenge to philosophical thinking. On its face, it repudiates many of the key features of the mechanical conception โฆ
๐ Original Info Title: ArXiv ID: 2512.18495 Date: Authors: Unknown ๐ Abstract Artificial intelligence techniques have achieved strong performance in classifying Windows Portable Executable (PE) malware, but their reliability often degrades under โฆ
๐ Original Info Title: ArXiv ID: 2512.18622 Date: Authors: Unknown ๐ Abstract Text2SQL, the task of generating SQL queries from natural language text, is a critical challenge in data engineering. Recently, Large Language Models (LLMs) have โฆ
๐ Original Info Title: ArXiv ID: 2512.18829 Date: Authors: Unknown ๐ Abstract Behavioral healthcare risk assessment remains a challenging problem due to the highly multimodal nature of patient data and the temporal dynamics of mood and affective โฆ
๐ Original Info Title: ArXiv ID: 2512.20061 Date: Authors: Unknown ๐ Abstract Content moderation at scale remains one of the most pressing challenges in today's digital ecosystem, where billions of user-and AI-generated artifacts must be continuously โฆ
๐ Original Info Title: ArXiv ID: 2512.19736 Date: Authors: Unknown ๐ Abstract The structure of topology underpins much of the research on performance and robustness, yet available topology data are typically scarce, necessitating the generation of โฆ
๐ Original Info Title: ArXiv ID: 2512.19663 Date: Authors: Unknown ๐ Abstract Diabetic retinopathy (DR) is a leading cause of preventable blindness worldwide, necessitating accurate automated diagnostic systems. While general-domain vision-language โฆ
๐ Original Info Title: ArXiv ID: 2512.20618 Date: Authors: Unknown ๐ Abstract Recent advances in multimodal LLMs and systems that use tools for long-video QA point to the promise of reasoning over hour-long episodes. However, many methods still โฆ
๐ Original Info Title: ArXiv ID: 2512.18092 Date: Authors: Unknown ๐ Abstract Neuron identification is a popular tool in mechanistic interpretability, aiming to uncover the human-interpretable concepts represented by individual neurons in deep โฆ
๐ Original Info Title: ArXiv ID: 2512.18552 Date: Authors: Unknown ๐ Abstract While current software agents powered by large language models (LLMs) and agentic reinforcement learning (RL) can boost programmer productivity, their training data (e.g., โฆ
๐ Original Info Title: ArXiv ID: 2512.18452 Date: Authors: Unknown ๐ Abstract Despite being one of the earliest neural network layers, the Multilayer Perceptron (MLP) is arguably one of the least understood parts of the transformer architecture due โฆ
๐ Original Info Title: ArXiv ID: 2512.18360 Date: Authors: Unknown ๐ Abstract We present a novel neurosymbolic framework for RDF-to-text generation, in which the model is "trained" through collaborative interactions among multiple LLM agents rather โฆ
๐ Original Info Title: ArXiv ID: 2512.18311 Date: Authors: Unknown ๐ Abstract Observability into the decision making of modern AI systems may be required to safely deploy increasingly capable agents. Monitoring the chain-of-thought (CoT) of today's โฆ
๐ Original Info Title: ArXiv ID: 2512.19726 Date: Authors: Unknown ๐ Abstract Reinforcement learning (RL) has achieved strong results, but deploying visual policies on resource-constrained edge devices remains challenging due to computational cost โฆ
๐ Original Info Title: ArXiv ID: 2512.17795 Date: Authors: Unknown ๐ Abstract The unprecedented proliferation of digital data presents significant challenges in access, integration, and value creation across all data-intensive sectors. Valuable โฆ
๐ Original Info Title: ArXiv ID: 2512.18190 Date: Authors: Unknown ๐ Abstract This paper proposes the External Hippocampus framework, which models language model reasoning from a cognitive dynamics perspective as the flow of information energy in โฆ
๐ Original Info Title: ArXiv ID: 2512.19817 Date: Authors: Unknown ๐ Abstract This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. image details and degrades visual quality, it also encodes information โฆ
๐ Original Info Title: ArXiv ID: 2512.18082 Date: Authors: Unknown ๐ Abstract Semantic segmentation of outdoor street scenes plays a key role in applications such as autonomous driving, mobile robotics, and assistive technology for visually-impaired โฆ
๐ Original Info Title: ArXiv ID: 2512.18564 Date: Authors: Unknown ๐ Abstract Figure 1: Vox Deorum is a hybrid LLM+X architecture for 4X strategy games. In the left panel, we see how the LLM strategist processes game state and sets high-level โฆ
๐ Original Info Title: ArXiv ID: 2512.20239 Date: Authors: Unknown ๐ Abstract Formalized the 2D hierarchical rectangle packing problem โข Proposed Multi-level Logic-based Benders Decomposition, outperforming monolithic and Bottom-Up methods ๐ Full โฆ
๐ Original Info Title: ArXiv ID: 2512.17910 Date: Authors: Unknown ๐ Abstract Modern large language model (LLM) systems increasingly rely on multi-turn pipelines that are composed of multiple task-specific adapters, yet existing serving frameworks โฆ
๐ Original Info Title: ArXiv ID: 2512.18616 Date: Authors: Unknown ๐ Abstract We present DASH (Deception-Augmented Shared mental model for Human-machine teaming), a novel framework that enhances mission resilience by embedding proactive deception โฆ
๐ Original Info Title: ArXiv ID: 2512.18489 Date: Authors: Unknown ๐ Abstract Large Language Models (LLMs) demonstrate strong fewshot generalization through in-context learning (ICL), yet their reasoning in dynamic and stochastic environments remains โฆ
๐ Original Info Title: ArXiv ID: 2512.20260 Date: Authors: Unknown ๐ Abstract Weakly-Supervised Camouflaged Object Detection (WSCOD) aims to locate and segment objects that are visually concealed within their surrounding scenes, relying solely on โฆ
๐ Original Info Title: ArXiv ID: 2512.18597 Date: Authors: Unknown ๐ Abstract A vision-based trajectory analysis solution is proposed to address the "zero-speed braking" issue caused by inaccurate Controller Area Network (CAN) signals in commercial โฆ
๐ Original Info Title: ArXiv ID: 2512.19995 Date: Authors: Unknown ๐ Abstract Large language models increasingly expose reasoning traces, yet their underlying cognitive structure and steps remain difficult to identify and analyze beyond surface-level โฆ
๐ Original Info Title: ArXiv ID: 2512.18732 Date: Authors: Unknown ๐ Abstract Concept learning becomes possible only when existing representations fail to account for experience. Most models of learning and inference, however, presuppose a fixed โฆ
๐ Original Info Title: ArXiv ID: 2512.20043 Date: Authors: Unknown ๐ Abstract Symmetry is fundamental to understanding physical systems, and at the same time, can improve performance and sample efficiency in machine learning. Both pursuits require โฆ
๐ Original Info Title: ArXiv ID: 2512.18352 Date: Authors: Unknown ๐ Abstract Early Rumor Detection (EARD) aims to identify the earliest point at which a claim can be accurately classified based on a sequence of social media posts. This is especially โฆ
๐ Original Info Title: ArXiv ID: 2512.18315 Date: Authors: Unknown ๐ Abstract Observational studies in fields such as epidemiology often rely on covariate adjustment to estimate causal effects. Classical graphical criteria, like the back-door โฆ
๐ Original Info Title: ArXiv ID: 2512.19937 Date: Authors: Unknown ๐ Abstract Recent research has explored using very large language models (LLMs) as proxies for humans in tasks such as simulation, surveys, and studies. While LLMs do not possess a โฆ
๐ Original Info Title: ArXiv ID: 2512.19753 Date: Authors: Unknown ๐ Abstract We introduce QMBench, a comprehensive benchmark designed to evaluate the capability of large language model agents in quantum materials research. This specialized benchmark โฆ
๐ Original Info Title: ArXiv ID: 2512.17941 Date: Authors: Unknown ๐ Abstract Digital twins (DTs) can enable precision healthcare by continually learning a mathematical representation of patientspecific dynamics. However, mission critical healthcare โฆ
๐ Original Info Title: ArXiv ID: 2512.18747 Date: Authors: Unknown ๐ Abstract Multimodal Large Language Models (MLLMs) deliver strong vision-language performance but at high computational cost, driven by numerous visual tokens processed by the Vision โฆ
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