Knowledge catalogue
arXiv:2511.07761v2 Announce Type: replace Abstract: High-altitude balloons (HABs) are common in scientific research due to their wide range of applications and low cost. Because of their nonlinear, un
arXiv:2609.03858v1 Announce Type: new Abstract: Attention mechanisms are central to modern foundation models, yet their training dynamics remain poorly understood, especially when the attention matric
arXiv:2601.10187v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved remarkable strides in multilingual translation but are hindered by a systemic cross-lingual verbosi
arXiv:2609.03595v1 Announce Type: cross Abstract: We investigate what makes synthetic OCR supervision transfer to real Thai documents and use the resulting insights to build Wayu-Paxa-OCR-Zero, a Thai
arXiv:2609.03322v1 Announce Type: new Abstract: Language models encounter typos, corrupted text, altered words, and disrupted token order, yet robustness is usually evaluated only through output behav
arXiv:2609.03985v1 Announce Type: cross Abstract: Zero-shot vision-language models (VLMs) are increasingly used as training-free species recognizers, but reported accuracy can reflect more than visual
arXiv:2609.03052v1 Announce Type: new Abstract: As services move online, trust institutions such as banks, lenders, and governments must verify the identity of remote users. Fraud detection tools are
arXiv:2602.22766v3 Announce Type: replace Abstract: Latent visual reasoning aims to mimic human's imagination process by meditating through hidden states of Multimodal Large Language Models. While rec
arXiv:2601.08955v3 Announce Type: replace-cross Abstract: Recent advances in world models have shown promise for modeling future dynamics of environmental states, enabling agents to reason and act wit
arXiv:2609.03186v1 Announce Type: cross Abstract: Training deep learning-based medical image segmentation models is challenging with limited curated datasets. For AGITG TOPGEAR, a gastric cancer trial
arXiv:2609.03210v1 Announce Type: cross Abstract: Artificial intelligence weather prediction (AIWP) systems now surpass state-of-the-art physical models for medium-range weather forecasting. Current g
arXiv:2609.03781v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in multilingual settings, yet their safety is still evaluated primarily in English. This limits our
arXiv:2609.03422v1 Announce Type: new Abstract: Diversity is a widely observed factor in the resilient function of collective systems, yet the type of diversity that matters depends on the properties
arXiv:2609.03883v1 Announce Type: new Abstract: Creatures that display 'hedonic place preference behaviour' are thought by many scientists to experience feelings, on the assumption that their attracti
arXiv:2609.04028v1 Announce Type: cross Abstract: The geometric morphology of deposited filaments can significantly influence the structural performance and stability of 3D concrete-printed (3DCP) str
arXiv:2609.04014v1 Announce Type: new Abstract: For trained operators, gauge reading requires little specialized knowledge, low cognitive effort, and high repeatability. Yet Multimodal Large Language
arXiv:2609.04024v1 Announce Type: new Abstract: Procedural instruction following is a basic requirement for controllable language-model systems, especially when generated trajectories are inspected or
arXiv:2609.03966v1 Announce Type: new Abstract: Agent evaluations report a tool-call rate read off the serving stack. That number can be zero while the model is emitting well-formed calls: the interfa
arXiv:2609.03329v1 Announce Type: cross Abstract: Long-duration gravitational-wave modelling must resolve fast orbital motion together with slow dissipative evolution while preventing small numerical
arXiv:2609.03967v1 Announce Type: cross Abstract: Several studies have evaluated the ability of Large Language Models (LLMs) for meal planning, yielding positive outcomes. These models can process nat
arXiv:2609.04030v1 Announce Type: new Abstract: IRWOZ has improved industrial human-robot interaction (HRI) dialogue systems through domain-specific annotations. However, its initial version contains
arXiv:2503.04997v4 Announce Type: replace Abstract: Automatic visual inspection using machine learning plays a key role in achieving zero-defect policies in industry. Research on anomaly detection is
arXiv:2609.03436v1 Announce Type: cross Abstract: Reasoning traces of large language models are widely read as containing 'breakthrough' moments and early-legible fates. Both readings rest on measurem
arXiv:2609.03181v1 Announce Type: new Abstract: We present Jina-OCR-v1, an end-to-end document parsing model built to serve on low-budget GPUs. It combines the compressed-vision encoder and the 3B mix
arXiv:2609.02942v1 Announce Type: cross Abstract: LLM-as-a-Judge pipelines are increasingly used to evaluate AI-generated text, based on the assumption that judgments arise from reasoning over candida
arXiv:2607.14415v2 Announce Type: replace Abstract: Computed Tomography (CT) carries significant ionizing radiation risks, driving the need for sparse-view reconstruction. Implicit scene representatio
arXiv:2609.03588v1 Announce Type: new Abstract: As LLMs increasingly act through tools, they must reconcile user instructions, parametric knowledge, and dynamic environmental observations before takin
arXiv:2609.03117v1 Announce Type: cross Abstract: Neural fields (NFs) map continuous coordinates to signals such as color or density, but fast high-quality reconstruction from sparse observations rema
arXiv:2603.12440v2 Announce Type: replace-cross Abstract: GPU kernel optimization challenges LLMs beyond standard coding tasks, as it requires an understanding of hardware architecture, parallel compu
arXiv:2609.03597v1 Announce Type: new Abstract: Land ownership in Bangladesh is recorded in Ana-Ganda-Kora-Kranti-Til, a base-16 positional fraction system with dedicated Unicode glyphs, no mainstream
arXiv:2609.04180v1 Announce Type: cross Abstract: Gaps remain in our understanding of how large language models (LLMs) acquire knowledge during pre-training. We posit that auxiliary views, reformulati
arXiv:2609.03742v1 Announce Type: cross Abstract: Video lectures are valuable educational resources, but their dense and lengthy formats often overwhelm novice learners. This difficulty stems from a f
arXiv:2609.03790v1 Announce Type: new Abstract: Athlete monitoring data may be recorded minute by minute throughout a match or training session, while injury information may only indicate whether the
arXiv:2609.03229v1 Announce Type: new Abstract: Networks describe systems in biology and beyond, from protein interactions and social relationships to power grids and citation records. Reasoning about
arXiv:2609.03577v1 Announce Type: new Abstract: Language models are commonly discussed as technical artefacts, but they are obviously shaped by the linguistic worlds conveyed by data during their trai
arXiv:2609.03334v1 Announce Type: new Abstract: A key bottleneck in 3D Gaussian Splatting training is the continual growth of Gaussian primitives, which increases optimization cost and slows convergen
arXiv:2609.03148v1 Announce Type: new Abstract: Most prior works focused on conflicts between an LLM's internal parametric knowledge and externally provided context. In contrast, we investigate how LL
arXiv:2609.04173v1 Announce Type: new Abstract: For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases.
arXiv:2609.03294v1 Announce Type: new Abstract: Latent world models support efficient model predictive control from high-dimensional observations, yet optimizing a single learned latent objective can
arXiv:2412.14626v3 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have demonstrated their potential in automating the scientific research ideation. Existing
arXiv:2609.03528v1 Announce Type: cross Abstract: Diffusion reinforcement learning (RL) has recently achieved significant success in post-training image and video generative models. However, most diff
arXiv:2609.03079v1 Announce Type: new Abstract: On-device LLM inference is attractive for privacy and responsiveness, but remains challenging on mobile and embedded devices because model weights far e
arXiv:2609.03069v1 Announce Type: new Abstract: Neural operators are fast, differentiable surrogates for physical simulation, but their accuracy often degrades when domain geometry, size, or operating
arXiv:2503.16551v4 Announce Type: replace Abstract: Control barrier functions (CBFs) provide a principled framework for safety-critical control, but their construction typically requires an explicit a
arXiv:2503.10421v2 Announce Type: replace Abstract: The application of learning based methods to vehicle routing problems has emerged as a pivotal area of research in combinatorial optimization. These
arXiv:2609.02969v1 Announce Type: cross Abstract: We present, to the best of our knowledge, the first publicly available resource for predicting left ventricular ejection fraction (EF) from parasterna
arXiv:2609.03343v1 Announce Type: cross Abstract: This paper addresses infinite-dimensional Bayesian inference for inverse problem of partial differential equations with model parameters in infinite-d
arXiv:2609.03206v1 Announce Type: cross Abstract: Using a zoom-in tool is an important foundational part of modern visual agents, because it allows to efficiently handle tasks involving high-resolutio
arXiv:2606.20954v2 Announce Type: replace-cross Abstract: Long-running language-model systems accumulate interaction history that outgrows the context window, so they must continually evict. When an e
arXiv:2609.04194v1 Announce Type: new Abstract: Reasoning traces from chain-of-thought models appear to offer a legible window into how a model arrives at its answer. A growing body of work treats the
arXiv:2609.03330v1 Announce Type: new Abstract: Moral language plays a central role in shaping online endorsement and the diffusion of information, yet existing moral foundation detection systems ofte
arXiv:2609.03594v1 Announce Type: cross Abstract: As integrated circuit technology scales into the nanometer regime, the traditional disconnect between logic synthesis and physical design has led to s
arXiv:2609.02954v1 Announce Type: new Abstract: Identifying the issues disputed between litigating parties is a crucial component of real-world litigation. However, legal issues remain comparatively u
arXiv:2505.00284v3 Announce Type: replace-cross Abstract: Rapid advances in vision-language models (VLMs) have generated growing interest in their application to autonomous driving. A prevailing assum
arXiv:2601.13989v2 Announce Type: replace Abstract: Neural networks trained by gradient-based methods often exhibit optimization-induced accuracy plateaus in scientific machine learning tasks. We pres
arXiv:2609.02940v1 Announce Type: cross Abstract: Recent automatic speech recognition (ASR) systems increasingly integrate large language models (LLMs) to leverage their semantic knowledge, either ext
arXiv:2609.03796v1 Announce Type: cross Abstract: We introduce LLaDA-Image, a unified framework that pairs a 6B Diffusion Transformer (DiT) trained from scratch with a frozen vision-language understan
arXiv:2503.03313v4 Announce Type: replace-cross Abstract: Text-Attributed Graphs (TAGs), where each node is associated with text descriptions, are ubiquitous in real-world scenarios. They typically ex
arXiv:2604.05460v2 Announce Type: replace-cross Abstract: Large language model (LLM) evaluation platforms increasingly rely on pairwise human judgments. These data are noisy, sparse, and non-uniform,
arXiv:2609.02931v1 Announce Type: cross Abstract: Scripted and rule-based non-player characters (NPCs) in combat video games often exhibit predictable behaviors that experienced players can exploit, w