Knowledge catalogue
arXiv:2608.08064v1 Announce Type: new Abstract: Learning fine-grained spatial patterns from coarse-resolution data is challenging, especially in causal settings where high-resolution effects must be i
arXiv:2608.09139v1 Announce Type: new Abstract: Video coding is advancing into the low and ultra-low bitrate regime, driven by end-to-end codecs that replace the hand-crafted pipeline with jointly opt
arXiv:2608.09282v1 Announce Type: new Abstract: Real-world shopping often requires constructing a basket of complementary items rather than retrieving a single product. Such combo-shopping tasks arise
arXiv:2608.07570v1 Announce Type: cross Abstract: Explainable aesthetic image cropping requires not only localizing a visually pleasing crop but also explaining why it is preferred. Existing crop-and-
arXiv:2603.29512v3 Announce Type: replace Abstract: The reliable operation of Unmanned Underwater Vehicle (UUV) clusters is highly dependent on continuous acoustic communication. However, this communi
arXiv:2608.07642v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human values remains a major challenge, especially for trustworthy AI. While existing approaches such as RLHF
arXiv:2608.09324v1 Announce Type: new Abstract: On unlabeled test data, reinforcement learning lacks a ground-truth reward; test-time RL methods derive one from the model's own roll-outs, rewarding th
arXiv:2608.09443v1 Announce Type: new Abstract: Large language model (LLM) agents can support medication review between clinical visits, but safe choices for older adults with multimorbidity depend on
arXiv:2608.09202v1 Announce Type: new Abstract: Modern autonomous vehicles are equipped with multiple sensors, such as cameras, LiDAR, and radar, for comprehensive environmental perception. However, r
arXiv:2608.08032v1 Announce Type: new Abstract: Safety alignment in multilingual models is uneven: a model that reliably refuses a harmful request in English will often comply with the same request in
arXiv:2608.09748v1 Announce Type: cross Abstract: Decentralization as a concept in computer science has existed for over half a century. Despite its fundamental role across domains such as security, d
arXiv:2608.07476v1 Announce Type: new Abstract: We develop a formal framework for constructing canonical interpretations from plural structure theories. A structure theory is a triple T = ({Sigma}, A,
arXiv:2608.08878v1 Announce Type: cross Abstract: Transformer-based large language models (LLMs) achieve strong performance across many tasks, but their Key-Value (KV) cache grows linearly with sequen
arXiv:2608.09024v1 Announce Type: new Abstract: Emergency-department (ED) triage requires clinicians to rapidly identify patients who need immediate attention, determine who can safely wait, and prior
arXiv:2608.09189v1 Announce Type: new Abstract: Despite significant advances in instruction-following and auditory comprehension, the evaluation of Emotional Intelligence (EI) in Spoken Language Model
arXiv:2608.09096v1 Announce Type: new Abstract: Large Language Models (LLMs) have driven rapid progress in autonomous agents, yet standard evaluations remain confined to static task solving. An emergi
arXiv:2608.07535v1 Announce Type: cross Abstract: Multi-modal large language models (MLLMs) integrate heterogeneous modalities through modality alignment and fusion, enabling stronger understanding an
arXiv:2608.08077v1 Announce Type: new Abstract: Theory of Space framework (ToS) assesses the spatial understanding of curiosity-driven Vision-Language Models (VLMs) under partial observability. As AI
arXiv:2510.23389v2 Announce Type: replace-cross Abstract: The behaviour of neural network components must be proven correct before deployment in safety-critical systems. Unfortunately, existing neural
arXiv:2608.08888v1 Announce Type: new Abstract: Autoregressive transformers compute along two axes: horizontally across generated tokens, and vertically through model depth. Dense attention gives each
arXiv:2608.07881v1 Announce Type: new Abstract: Clustering mixed tabular data requires a unified metric space to bridge the inherent heterogeneity between continuous numerical measurements and discret
arXiv:2608.09332v1 Announce Type: new Abstract: Hallucinations are a major concern for the integration of artificial intelligence into medicine, although less explored in the realm of medical image pr
arXiv:2608.08466v1 Announce Type: new Abstract: Modern LLM agents are often improved by modifying prompts, tools, or workflows manually, while the executable scaffold surrounding the model---the harne
arXiv:2608.08871v1 Announce Type: new Abstract: This paper addresses autonomous intervention with an underwater vehicle--manipulator system (UVMS) in confined, cluttered, and partially known environme
arXiv:2607.18867v2 Announce Type: replace-cross Abstract: Large language models leak parametric knowledge of what followed a historical date into decision tasks indexed by that date -- not necessarily
arXiv:2608.09019v1 Announce Type: cross Abstract: As generative AI increasingly becomes a common source of daily decision-making, including financial choices, it is critical to understand how people e
arXiv:2608.08069v1 Announce Type: cross Abstract: Foundation models are increasingly reused as software components, making model selection a critical software-engineering decision. Current model hubs
Heeeey all! I just completed some fun tests with Muse Glimmer, I thought I'd let you know. In fact, the summary below was written by Muse itself! I ran a 2× DGX Spark cluster and got Meta's day-old Mu
arXiv:2608.07688v1 Announce Type: new Abstract: IT audits require auditors to judge whether heterogeneous organizational evidence satisfies semantic security and compliance controls. This judgment is
arXiv:2511.10119v4 Announce Type: replace Abstract: We propose a new perspective for approaching artificial general intelligence (AGI) through an intelligence foundation model (IFM). Unlike existing f
arXiv:2608.07498v1 Announce Type: cross Abstract: Autonomous AI agents in social media present concrete risks to democratic discourse and platform governance, while also offering tools for pre-deploym
arXiv:2608.07520v1 Announce Type: cross Abstract: Mass religious gatherings such as the Kumbh Mela concentrate tens of millions of people into a single region over a few weeks, producing intense, repe
arXiv:2604.03480v2 Announce Type: replace-cross Abstract: Creative thinking is a fundamental aspect of human cognition, and divergent thinking-the capacity to generate novel and varied ideas-is widely
arXiv:2601.08856v3 Announce Type: replace-cross Abstract: Unit tests are critical in the hardware design lifecycle to ensure that component design modules are functionally correct and conform to the s
arXiv:2604.05695v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in 2D visual tasks but still struggle to understand physical space in rea
arXiv:2503.06211v3 Announce Type: replace-cross Abstract: Text-pretrained language models (LMs) encode rich world knowledge, but adapting them to process and generate perceptual modalities such as aud
arXiv:2608.08721v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by drafting multiple tokens for parallel verification, with efficiency critically dete
arXiv:2508.09125v4 Announce Type: replace Abstract: Instruction following has catalyzed the recent era of Large Language Models (LLMs) and is the foundational skill underpinning more advanced capabili
arXiv:2608.09723v1 Announce Type: new Abstract: Recent graphical user interface (GUI) grounders have significantly advanced single-shot accuracy on standard benchmarks, yet their performance degrades
arXiv:2507.03162v2 Announce Type: replace-cross Abstract: The rapid advancement of Large Language Models (LLMs) has transformed various domains, particularly computer science (CS) education. These mod
arXiv:2403.10232v2 Announce Type: replace-cross Abstract: Conventional matrix completion methods approximate the missing values by assuming the matrix to be low-rank, which leads to a linear approxima
These numbers were captured during a real feature implementation task in Next.js and Nest.js (adding a theme switching system across components). The structural predictability of UI/state refactoring
arXiv:2608.08567v1 Announce Type: new Abstract: A central obstacle in building graph foundation models is the input heterogeneity in terms of feature space dimensionality, semantics, and structure. Su
arXiv:2608.09636v1 Announce Type: cross Abstract: Accurate 3D neuron segmentation in fluorescence microscopy is critical for neuroscience. However, the sparse and elongated morphology of neurons poses
arXiv:2608.08118v1 Announce Type: new Abstract: There are several methods for searching for graphs with prescribed properties, such as SAT solvers and specialized generators. These methods return the
arXiv:2608.09227v1 Announce Type: new Abstract: Omnimodal language models (OLMs) enable unified audio-visual understanding, but processing long joint token sequences makes inference computationally pr
arXiv:2608.08775v1 Announce Type: new Abstract: Agentic benchmarks aim to measure how well AI agents plan, search, execute, and recover within realistic multi-tool environments, but they are almost ex
arXiv:2608.09666v1 Announce Type: new Abstract: Recent advances in visual generative models have enabled high-quality image and video generation, but evaluating these models often demands sampling hun
Something happened today that I think most people are going to miss because there are two separate stories and neither one is getting the full picture. OpenAI expanded Daybreak. If you haven't heard o
arXiv:2608.08557v1 Announce Type: new Abstract: Visual tool use has emerged as a fundamental capability for multimodal agents to actively acquire evidence beyond a fixed image encoding. The prevailing
OWN YOUR INTELLIGENCE Last year, building on open-weight models was primarily a cost rationalization exercise. Slightly worse performance for a much cheaper price. Now, it is increasingly an existenti
arXiv:2608.09805v1 Announce Type: cross Abstract: Exploration has been a focus of reinforcement learning research for a long time. Recently, there has been growing evidence that it is also an importan
arXiv:2608.09931v1 Announce Type: new Abstract: Self-improvement for multimodal large language models (MLLMs) is typically driven by reward-based methods that provide only coarse scalar feedback. Dist
arXiv:2608.07509v1 Announce Type: cross Abstract: LLMs are increasingly used for conversational tutoring, but effective tutoring requires more than correct answers. Tutors must choose when to scaffold
arXiv:2608.07478v1 Announce Type: cross Abstract: India's 22 official languages create a critical accessibility barrier: the majority of medical documentation exists exclusively in English, yet the pa
arXiv:2508.06706v2 Announce Type: replace Abstract: Rule-based methods for knowledge graph completion provide explainable results, but often require tens of thousands of rules to achieve competitive p
arXiv:2512.22966v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated promise in medical knowledge assessments, yet their practical utility in real-world clinical decision
arXiv:2607.11505v2 Announce Type: replace-cross Abstract: Post-training for large language models typically couples policy exploration with model optimization, hindering the reuse of high-reward behav
arXiv:2511.09373v2 Announce Type: replace-cross Abstract: LLMs now tackle a wide range of software-related tasks, yet we show that their performance varies markedly both across and within these tasks.
arXiv:2601.22510v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often achieve strong benchmark accuracy yet remain brittle under small distribution shifts. While recent mechanis