Knowledge catalogue
arXiv:2606.18069v2 Announce Type: replace-cross Abstract: A surface representation suitable for geometry processing should be compact and explicit, provide global smoothness guarantees, support a wide
arXiv:2609.02450v1 Announce Type: new Abstract: Semantic triggers in federated learning (FL) can be less conspicuous than synthetic patches, but sample-dependent placement may weaken backdoor implanta
arXiv:2609.01991v1 Announce Type: new Abstract: Magnetic core loss originates in the hysteresis loop: the energy dissipated per excitation cycle equals the loop area, and frequency, temperature, and w
arXiv:2510.20820v4 Announce Type: replace Abstract: Existing personalized image generators still struggle to preserve multiple reference identities in natural and coherent multi-human generations. To
arXiv:2609.01746v1 Announce Type: new Abstract: Flow Matching has emerged as a leading framework for generative modeling, powering state-of-the-art systems such as FLUX and Stable Diffusion 3.5. Howev
arXiv:2609.02184v1 Announce Type: new Abstract: Dynamic four-dimensional (4D) Gaussian Splatting has emerged as a powerful explicit representation for high-quality view synthesis, yet existing methods
arXiv:2609.01673v1 Announce Type: cross Abstract: Activity-cliff ranking remains difficult because local structural changes can cause large activity differences, while high-quality data that resolve t
arXiv:2310.05288v4 Announce Type: replace-cross Abstract: Matrix-variate distributions are a relatively recent addition to the model-based clustering literature, thereby making it possible to analyze
arXiv:2609.02620v1 Announce Type: new Abstract: Generative AI is changing how cultural artifacts are created and circulated, and with it our understanding of creativity itself. Researchers disagree ab
Congratulations to @224ventureshq co-founder @ylecun on being named to the @TIME 100 AI 2026 list. Yann has spent four decades quietly building the foundations the rest of the field now stands on — fr
arXiv:2609.02306v1 Announce Type: new Abstract: Accurate joint encoder offsets are essential for kinematic consistency in humanoid lower limbs, yet existing calibration methods typically require exter
arXiv:2609.01925v1 Announce Type: cross Abstract: The attention prefilling phase of long-context LLM inference scales quadratically, making self-attention a severe computational bottleneck. Traditiona
arXiv:2609.01840v1 Announce Type: new Abstract: Spontaneous movement is one of the earliest windows onto an infant's neuromotor health, and structured clinical instruments that score it are validated
arXiv:2306.06865v2 Announce Type: replace-cross Abstract: Clinical guidelines underscore the importance of regularly monitoring and surveilling arteriovenous fistula (AVF) access in hemodialysis patie
arXiv:2609.02468v1 Announce Type: cross Abstract: We explore predicting eCommerce user preferences for product aspects such as brand, size, and color - a task we define as Aspect Affinity. Solving thi
arXiv:2609.02003v1 Announce Type: new Abstract: Fully-powered knee prostheses, unlike traditional passive knees, can perform controlled positive work, reducing the need for compensatory behaviors by u
arXiv:2609.01799v1 Announce Type: cross Abstract: Many current end-to-end driving policies emit a pool of candidate trajectories and select one, which makes selection a separable component: a scorer c
arXiv:2609.02028v1 Announce Type: new Abstract: Despite recent advances in large vision-language models (LVLMs), object hallucination remains a major barrier to their reliable deployment. Existing det
arXiv:2609.02315v1 Announce Type: cross Abstract: A single sentence often expresses multiple valid relational triplets, which makes Open Information Extraction (OpenIE) fundamentally a multi-output ta
arXiv:2609.02288v1 Announce Type: new Abstract: Diffusion MRI requires repeated k-space acquisitions over multiple diffusion-encoding directions, making acquisition time dependent on both spatial and
arXiv:2609.02659v1 Announce Type: cross Abstract: The pairwise independent correlation gap is the ratio of the maximum expected value of a set function under arbitrary dependence to that under pairwis
arXiv:2609.02796v1 Announce Type: new Abstract: Sign language processing systems have traditionally operated at the sentence level, ignoring critical discourse phenomena fundamental to sign language c
arXiv:2609.02111v1 Announce Type: cross Abstract: Dermatology artificial intelligence (AI) models are predominantly trained on light-skinned, cancer-focused image collections, yet they are increasingl
arXiv:2609.01794v1 Announce Type: new Abstract: How do learners avoid overgeneralizations such as Tom laughed me without explicit negative evidence? Constructionists have posited two proposals that de
arXiv:2609.02685v1 Announce Type: cross Abstract: RAG has become the de facto method for incorporating new, corpus-specific knowledge into an instruction following LLM (Instruct LLM). Although RAG-bas
arXiv:2606.17350v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have enabled the generation of high-quality prose, yet whether these models are capable of gen
arXiv:2609.02275v1 Announce Type: cross Abstract: Large language models are trained to model conditional distributions over text, yet it remains inadequately understood whether they capture the full d
arXiv:2408.02932v3 Announce Type: replace-cross Abstract: Clustering is a fundamental task in machine learning and data science, and similarity graph-based clustering is an important approach within t
arXiv:2609.02797v1 Announce Type: cross Abstract: People increasingly use language models to support life decisions. Many such decisions involve a probabilistic forecast: How likely is a major life ev
arXiv:2511.11659v3 Announce Type: replace Abstract: To address insufficient accuracy in multi-scale segmentation for agricultural habitat recognition, this study proposes a Dynamic Weighted Feature Fu
arXiv:2603.06662v3 Announce Type: replace Abstract: Continual VideoQA with multimodal LLMs remains challenging because sequential adaptation induces task interference, while storing task-specific prom
arXiv:2602.02028v3 Announce Type: replace Abstract: Enabling artificial intelligence systems, particularly large language models, to update knowledge and flexibly apply it during reasoning remains a c
arXiv:2609.02839v1 Announce Type: new Abstract: Adverse weather conditions such as rain, haze, and snow significantly degrade image quality, posing challenges for both human perception and physical AI
arXiv:2503.22411v2 Announce Type: replace Abstract: Is political incivility rising across democracies - and if so, why? Analysing approximately 13.8 million tweets from parliamentarians in 26 countrie
arXiv:2606.13081v2 Announce Type: replace-cross Abstract: Emotion significantly influences cognition, enhancing memory and learning under certain conditions. Drawing on this principle, emotion-augment
arXiv:2412.01865v5 Announce Type: replace-cross Abstract: BrainAGE is a promising imaging-derived biomarker of neurobiological ageing and disease risk, yet current approaches rely predominantly on T1-
arXiv:2510.07277v2 Announce Type: replace Abstract: Diabetic Macular Edema (DME) is a leading cause of vision loss among patients with Diabetic Retinopathy (DR). While deep learning has shown promisin
arXiv:2609.01742v1 Announce Type: new Abstract: Anti-UAV systems increasingly fuse multiple sensors, yet their detection heads provide no per-modality reliability signal. This study evaluates whether
arXiv:2609.02155v1 Announce Type: new Abstract: The Johnson-Lindenstrauss (JL) lemma guarantees that a random projection of n points to m=O(arepsilon^{-2}log n) dimensions preserves pairwise squared d
arXiv:2609.02222v1 Announce Type: new Abstract: Foot forward kinematics (FK) is widely used to improve proprioceptive legged odometry by providing reliable velocity constraints during foot support. Ex
arXiv:2609.02262v1 Announce Type: cross Abstract: Ragebait refers to online content intentionally designed to provoke anger or outrage and thereby increase attention and engagement. However, reliable
arXiv:2609.02640v1 Announce Type: new Abstract: The rapid advancement of generative models has significantly worsened the problem of manipulated image detection, as these methods are capable of produc
arXiv:2609.01655v1 Announce Type: cross Abstract: Unified recommendation models aim to jointly model non-sequential multi-field features and sequential user behaviors, but existing interaction-centric
arXiv:2609.02679v1 Announce Type: cross Abstract: When LLMs support public-facing or high-stakes workflows, missed fabrications can harm users and institutions, while false alarms consume limited huma
arXiv:2609.02212v1 Announce Type: new Abstract: Ensuring the reliability of deep learning models in real-time industrial defect detection is critical for high-stakes quality inspection. To mine uncert
arXiv:2609.02813v1 Announce Type: new Abstract: Text-to-image models excel at natural image synthesis but struggle with graphic design, where success depends on satisfying precise constraints on typog
arXiv:2609.02600v1 Announce Type: new Abstract: This work presents an approach to the Generalizability Across Tumors (BraTS-GoAT) task of the BraTS 2026 Challenge, which focuses on robust segmentation
arXiv:2309.06349v2 Announce Type: replace-cross Abstract: Thompson sampling (TS) is one of the most popular and earliest algorithms to solve stochastic multi-armed bandit problems. We consider a varia
arXiv:2603.03718v2 Announce Type: replace Abstract: Glass surface segmentation from RGB images is a challenging task, with a number of applications in robotics and scene understanding. As glass lacks
arXiv:2511.08590v2 Announce Type: replace Abstract: Large Language Model (LLM) routing has demonstrated strong capability in balancing response quality with computational cost. As users exhibit divers
GPT-6 Astra by @OpenAI achieves SOTA on ARC-AGI: - Astra scores 63% on ARC-AGI-3, 99% via a new provider adapter harness - It surpasses human performance on 96% of ARC-AGI-3 levels - It builds the mos
arXiv:2406.05033v3 Announce Type: replace Abstract: We study gradient descent (GD) dynamics on logistic regression problems with large, constant step sizes. For linearly-separable data, it is known th
arXiv:2609.02881v1 Announce Type: new Abstract: We introduce the Graph Machine (GM), an architecture that maintains an O(n)-sized state and accesses it through sparse, dynamic routing. Unlike methods
arXiv:2609.02251v1 Announce Type: new Abstract: Handwriting trajectory recovery aims to infer the dynamic writing process hidden behind a static handwritten image. Since offline handwriting preserves
arXiv:2609.01730v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) allows a server to run a language model directly on encrypted user prompts, but current approaches remain prohibiti
arXiv:2607.01535v2 Announce Type: replace Abstract: Despite the intense engagement surrounding low-level vision generalist models, their effectiveness in zero/few-shot scenarios beyond learned tasks r
arXiv:2609.02746v1 Announce Type: cross Abstract: Polymeric materials are central to modern technologies, with applications ranging from energy to health and transportation. Although AI has made signi
arXiv:2609.01807v1 Announce Type: cross Abstract: Large language models (LLMs) achieve state-of-the-art generative ranking quality, but the ranking they produce must be decoded, and autoregressive dec
arXiv:2609.02015v1 Announce Type: new Abstract: Instruction-tuning data are judged by quality metrics, and tuned models are judged by benchmarks, but both judgments pass through an output interface: t
arXiv:2609.02138v1 Announce Type: cross Abstract: Stochastic gradient Markov chain Monte Carlo (SGMCMC) methods enable scalable Bayesian inference, but their performance depends strongly on hyperparam