๐ Original Info Title: ArXiv ID: 2512.20573 Date: Authors: Unknown ๐ Abstract Diffusion Large Language Models (dLLMs) offer fast, parallel token generation, but their standalone use is plagued by an inherent efficiencyquality tradeoff. We show that, โฆ
๐ Original Info Title: ArXiv ID: 2512.21494 Date: Authors: Unknown ๐ Abstract Humor is a salient testbed for human-like creative thinking in large language models (LLMs). We study humor using the Japanese creative response game Oogiri, in which โฆ
๐ Original Info Title: ArXiv ID: 2512.22671 Date: Authors: Unknown ๐ Abstract Structured width pruning of GLU-MLP layers in Llama-3.2 models, guided by the Maximum Absolute Weight (MAW) criterion, reveals a systematic dichotomy in how reducing the โฆ
๐ Original Info Title: ArXiv ID: 2512.20884 Date: Authors: Unknown ๐ Abstract Autonomous agents powered by large language models (LLMs), often enhanced by retrieval-augmented generation (RAG), are powerful processors of digital content. However, RAG โฆ
๐ Original Info Title: ArXiv ID: 2512.22876 Date: Authors: Unknown ๐ Abstract Modern AI systems often comprise multiple learnable components that can be naturally organized as graphs. A central challenge is the end-to-end training of such systems โฆ
๐ Original Info Title: ArXiv ID: 2512.20996 Date: Authors: Unknown ๐ Abstract Traffic simulation is important for transportation optimization and policy making. While existing simulators such as SUMO and MAT-Sim offer fully-featured platforms and โฆ
๐ Original Info Title: ArXiv ID: 2512.20941 Date: Authors: Unknown ๐ Abstract Data-driven surrogate models are increasingly adopted to accelerate vehicle design. However, open-source multi-fidelity datasets and empirical guidelines linking dataset โฆ
๐ Original Info Title: ArXiv ID: 2512.20629 Date: Authors: Unknown ๐ Abstract This study proposes a multi-agent language framework that enables continual strategy evolution without fine-tuning the language model's parameters. The core idea is to โฆ
๐ Original Info Title: ArXiv ID: 2512.11942 Date: Authors: Unknown ๐ Abstract Differences in perception, information asymmetries, and bounded rationality lead game-theoretic players to derive a private, subjective view of the game that may diverge โฆ
๐ Original Info Title: ArXiv ID: 2512.20670 Date: Authors: Unknown ๐ Abstract Prevalent multimodal fake news detection relies on consistency-based fusion, yet this paradigm fundamentally misinterprets critical cross-modal discrepancies as noise, โฆ
๐ Original Info Title: ArXiv ID: 2512.20296 Date: Authors: Unknown ๐ Abstract Figure 1. Overview of TAVID framework. Given a text dialogue and reference images, TAVID simultaneously produces interactive videos and conversational speech with natural โฆ
๐ Original Info Title: ArXiv ID: 2512.20627 Date: Authors: Unknown ๐ Abstract Intent-Based Networking (IBN) offers a promising paradigm for intelligent and automated network control in Industrial Internet of Things (IIoT) environments by translating โฆ
๐ Original Info Title: ArXiv ID: 2512.21373 Date: Authors: Unknown ๐ Abstract We introduce AInsteinBench, a large-scale benchmark for evaluating whether large language model (LLM) agents can operate as scientific computing development agents within โฆ
๐ Original Info Title: ArXiv ID: 2512.20920 Date: Authors: Unknown ๐ Abstract Full Fine-Tuning is a pivotal technique for adapting Large Language Models (LLMs) to downstream tasks, yet it incurs substantial memory overhead due to the necessity of โฆ
๐ Original Info Title: ArXiv ID: 2512.20943 Date: Authors: Unknown ๐ Abstract Free-viewpoint video (FVV) enables immersive viewing experiences by allowing users to view scenes from arbitrary perspectives. As a prominent reconstruction technique for โฆ
๐ Original Info Title: ArXiv ID: 2512.20904 Date: Authors: Unknown ๐ Abstract We propose an efficient method to compute a small set of integer-constrained cone singularities, which induce a rotationally seamless conformal parameterization with low โฆ
๐ Original Info Title: ArXiv ID: 2512.21514 Date: Authors: Unknown ๐ Abstract Elephant in the style of Jeff koonz A highly detailed digital portrait of an anime otoko no ko, with androgynous features and intricate clothing, standing in a bustling โฆ
๐ Original Info Title: ArXiv ID: 2512.22692 Date: Authors: Unknown ๐ Abstract Existing machine learning frameworks operate over the field of real numbers (R) and learn representations in real (Euclidean or Hilbert) vector spaces (e.g., R d ). Their โฆ
๐ Original Info Title: ArXiv ID: 2512.21709 Date: Authors: Unknown ๐ Abstract Large language models (LLMs) can produce text that closely resembles human writing. This capability raises concerns about misuse, including disinformation and content โฆ
๐ Original Info Title: ArXiv ID: 2512.22491 Date: Authors: Unknown ๐ Abstract As an endangered language, Manchu presents unique challenges for speech synthesis, including severe data scarcity and strong phonological agglutination. This paper proposes โฆ
๐ Original Info Title: ArXiv ID: 2512.22878 Date: Authors: Unknown ๐ Abstract The recent integration of artificial intelligence into medical imaging has driven remarkable advances in automated organ segmentation. However, most existing 3D โฆ
๐ Original Info Title: ArXiv ID: 2512.20325 Date: Authors: Unknown ๐ Abstract Exterior powers play important roles in persistent homology in computational geometry. In the present paper we study the problem of extracting the K longest intervals of โฆ
๐ Original Info Title: ArXiv ID: 2512.20983 Date: Authors: Unknown ๐ Abstract Large language models (LLMs) are increasingly evaluated in clinical settings using multi-dimensional rubrics which quantify reasoning quality, safety, and โฆ
๐ Original Info Title: ArXiv ID: 2512.22664 Date: Authors: Unknown ๐ Abstract In the big data era, the computer vision field benefits from large-scale datasets such as LAION-2B, LAION-400M, and ImageNet-21K, Kinetics, on which popular models like the โฆ
๐ Original Info Title: ArXiv ID: 2512.22336 Date: Authors: Unknown ๐ Abstract Symbolic world models (e.g., PDDL domains or executable simulators) are central to model-based planning, but training LLMs to generate such world models is limited by the โฆ
๐ Original Info Title: ArXiv ID: 2512.20595 Date: Authors: Unknown ๐ Abstract We introduce Cube Bench, a Rubik's-cube benchmark for evaluating spatial and sequential reasoning in multimodal large language models (MLLMs). The benchmark decomposes โฆ
๐ Original Info Title: ArXiv ID: 2512.22420 Date: Authors: Unknown ๐ Abstract Speculative decoding (SD) accelerates LLM inference by verifying draft tokens in parallel. However, this method presents a critical trade-off: it improves throughput in โฆ
๐ Original Info Title: ArXiv ID: 2512.20669 Date: Authors: Unknown ๐ Abstract Cardiac rehabilitation constitutes a structured clinical process involving multiple interdependent phases, individualized medical decisions, and the coordinated โฆ
๐ Original Info Title: ArXiv ID: 2512.20714 Date: Authors: Unknown ๐ Abstract Generative AI enables personalized computer science education at scale, yet questions remain about whether such personalization supports or undermines learning. This โฆ
๐ Original Info Title: ArXiv ID: 2512.20665 Date: Authors: Unknown ๐ Abstract Partially miscible bubble populations trapped in porous media are ubiquitous in subsurface applications such as underground hydrogen storage (UHS), where cyclic injections โฆ
๐ Original Info Title: ArXiv ID: 2512.21446 Date: Authors: Unknown ๐ Abstract Masked diffusion language models (MDLMs) offer the potential for parallel token generation, but most open-source MDLMs decode fewer than 5 tokens per model forward pass โฆ
๐ Original Info Title: ArXiv ID: 2512.20381 Date: Authors: Unknown ๐ Abstract Service-based architecture (SBA) has recently gained attention in both industry and academia, primarily as a way to modernize legacy systems. It refers to a design style โฆ
๐ Original Info Title: ArXiv ID: 2512.21221 Date: Authors: Unknown ๐ Abstract Retrieving images from natural language descriptions is a core task at the intersection of computer vision and natural language processing, with wide-ranging applications โฆ
๐ Original Info Title: ArXiv ID: 2512.20675 Date: Authors: Unknown ๐ Abstract Learning generalizable reward functions is a core challenge in embodied intelligence. Recent work leverages contrastive vision language models (VLMs) to obtain dense, โฆ
๐ Original Info Title: ArXiv ID: 2512.22795 Date: Authors: Unknown ๐ Abstract Clinical notes are often stored in unstructured or semi-structured formats after extraction from electronic medical record (EMR) systems, which complicates their use for โฆ
๐ Original Info Title: ArXiv ID: 2512.22742 Date: Authors: Unknown ๐ Abstract Column Type Annotation (CTA) is a fundamental step towards enabling schema alignment and semantic understanding of tabular data. Existing encoder-only language models โฆ
๐ Original Info Title: ArXiv ID: 2512.13102 Date: Authors: Unknown ๐ Abstract Large language Models (LLMs) are usually used to answer questions, but many high-stakes applications (e.g., tutoring, clinical support) require the complementary skill of โฆ
๐ Original Info Title: ArXiv ID: 2512.22621 Date: Authors: Unknown ๐ Abstract Progress in automatic chord recognition has been slow since the advent of deep learning in the field. To understand why, I conduct experiments on existing methods and test โฆ
๐ Original Info Title: ArXiv ID: 2512.20407 Date: Authors: Unknown ๐ Abstract Unmanned aerial vehicles (UAVs), commonly known as drones, are increasingly used across diverse domains, including logistics, agriculture, surveillance, and defense. While โฆ
๐ Original Info Title: ArXiv ID: 2512.21106 Date: Authors: Unknown ๐ Abstract Graph-structured data exhibit substantial heterogeneity in where their predictive signals originate: in some domains, node-level semantics dominate, while in others, โฆ
๐ Original Info Title: ArXiv ID: 2512.22678 Date: Authors: Unknown ๐ Abstract Anthropogenic climate change has altered large-scale climate teleconnections, affecting regional temperatures. โข Changes to the teleconnections of ENSO, the IOD, and PDO โฆ
๐ Original Info Title: ArXiv ID: 2512.22705 Date: Authors: Unknown ๐ Abstract Hope speech has been relatively underrepresented in Natural Language Processing (NLP). Current studies are largely focused on English, which has resulted in a lack of โฆ
๐ Original Info Title: ArXiv ID: 2512.22605 Date: Authors: Unknown ๐ Abstract The precise prediction of human mobility has produced significant socioeconomic impacts, such as location recommendations and evacuation suggestions. However, existing โฆ
๐ Original Info Title: ArXiv ID: 2512.21354 Date: Authors: Unknown ๐ Abstract Contemporary large language model (LLM) agents are remarkably capable, but they still lack reliable safety controls and can produce unconstrained, unpredictable, and even โฆ
๐ Original Info Title: ArXiv ID: 2512.20636 Date: Authors: Unknown ๐ Abstract Many self-attention sublayers in large language models (LLMs) can be removed with little to no loss. We attribute this to the Attention Suppression Hypothesis: during โฆ
๐ Original Info Title: ArXiv ID: 2512.21201 Date: Authors: Unknown ๐ Abstract ๐ Full Content Zero-shot object navigation (ZSON) requires a robot to locate a target object in a previously unseen environment without relying on pre-built maps or โฆ
๐ Original Info Title: ArXiv ID: 2512.20624 Date: Authors: Unknown ๐ Abstract This study introduces a quantum-inspired framework for optimizing the exploration-exploitation tradeoff in multi-agent reinforcement learning (MARL), applied to โฆ
๐ Original Info Title: ArXiv ID: 2512.11920 Date: Authors: Unknown ๐ Abstract Large Language Models (LLMs) have revolutionized natural language processing tasks, but their deployment in datacenter environments faces significant challenges due to the โฆ
๐ Original Info Title: ArXiv ID: 2512.22473 Date: Authors: Unknown ๐ Abstract Our companion paper (Paper I) establishes that neural sequence models can implement exact Bayesian inference, with success depending on whether the architecture realizes โฆ
๐ Original Info Title: ArXiv ID: 2512.12381 Date: Authors: Unknown ๐ Abstract Intelligent systems are widely assumed to improve through learning, coordination, and optimization. However, across domains-from artificial intelligence to economic โฆ
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