Knowledge catalogue
Chipmaking equipment giant Applied Materials Inc. is expecting stronger sales this year compared with what it originally forecast, thanks to surging demand for artificial intelligence chips. The compa
arXiv:2605.15132v1 Announce Type: new Abstract: Autonomous multi-agent systems based on large language models (LLMs) have demonstrated remarkable abilities in independently solving complex tasks in a
arXiv:2605.14672v1 Announce Type: new Abstract: Estimating an N imes N quantum kernel from circuit fidelities requires Theta(N^2 S) measurement shots, the dominant bottleneck for deployment on near-te
arXiv:2605.14518v1 Announce Type: new Abstract: Activation functions are central to deep networks, influencing non-linearity, feature learning, convergence, and robustness. This paper proposes the Ada
arXiv:2605.14255v1 Announce Type: cross Abstract: Industrial visual inspection systems increasingly rely on deep classifiers whose heatmap explanations may appear visually plausible while failing to i
arXiv:2605.14322v1 Announce Type: new Abstract: Language agents are increasingly deployed in complex professional workflows, with tutoring emerging as a particularly high-stakes capability that remain
arXiv:2605.14689v1 Announce Type: new Abstract: Deep learning has profoundly impacted domains such as computer vision and natural language processing by uncovering complex patterns in vast datasets. H
arXiv:2605.13877v1 Announce Type: cross Abstract: We present ARES-LSHADE, a memetic differential-evolution variant submitted to the GECCO 2026 competition on LLM-designed evolutionary algorithms for t
arXiv:2602.11626v2 Announce Type: replace-cross Abstract: Learning solution operators for systems with complex, varying geometries and parametric physical settings is a central challenge in scientific
arXiv:2605.15187v1 Announce Type: new Abstract: A bottleneck in learning to understand articulated 3D objects is the lack of large and diverse datasets. In this paper, we propose to leverage large lan
arXiv:2605.14242v1 Announce Type: cross Abstract: The monitoring of fetal heart rate (FHR) and the assessment of its variability are crucial for preventing fetal compromise and adverse outcomes. Howev
arXiv:2602.15249v2 Announce Type: replace-cross Abstract: This study examines the distribution of Artificial Intelligence (AI) research across European NUTS-3 regions during the period 2015-2024. Usin
Samantha Cole / 404 Media: ArXiv, the repository of preprint academic research, says it will ban authors for a year if their papers have “incontrovertible evidence” of AI-generated work — The change c
ArXiv, a popular platform for preprint academic research, is taking a new step to attempt to reduce the volume of papers that include AI slop. If a paper has 'incontrovertible evidence that the author
As inference workloads dominate, what if these matmuls could also perform useful work and generate beneficial byproducts!? Similar to all the byproducts we get from crude oil distillation that are not
arXiv:2605.14211v1 Announce Type: new Abstract: Long-horizon embodied tasks remain a fundamental challenge in AI, as current methods rely on hand-engineered rewards or action-labeled demonstrations, n
arXiv:2605.14512v1 Announce Type: cross Abstract: Generative Recommendation (GenRec) models reformulate recommendation as a sequence generation task, representing items as discrete Semantic IDs used s
arXiv:2605.15198v1 Announce Type: cross Abstract: Visual reasoning, often interleaved with intermediate visual states, has emerged as a promising direction in the field. A straightforward approach is
arXiv:2605.13897v1 Announce Type: cross Abstract: We propose a novel multimodal deep learning framework for patient-level survival prediction, which integrates whole-slide histology features, RNA-seq
arXiv:2605.14073v1 Announce Type: cross Abstract: Deep neural networks have achieved strong performance in genomic sequence classification; however, relating their predictions to biologically meaningf
arXiv:2605.05686v2 Announce Type: replace Abstract: Language models draw on two knowledge sources: facts baked into weights (parametric memory, PM) and information in context (working memory, WM). We
arXiv:2605.14231v1 Announce Type: cross Abstract: Audio self-supervised learning (SSL) aims to learn general-purpose representations from large-scale unlabeled audio data. While recent advances have b
arXiv:2605.14271v1 Announce Type: new Abstract: LLM agents increasingly run inside execution harnesses that dispatch tools, allocate resources, and route messages between specialized components. Howev
Aujourd'hui je déconstruis la déconstruction. La déconstruction est le virus mental le plus efficace jamais conçu contre une civilisation. Il a été fabriqué en France entre 1966 et 1980 par trois homm
arXiv:2506.01015v2 Announce Type: replace Abstract: Segment Anything Model 2 (SAM2) exhibits strong generalisation for promptable segmentation in video clips; however, its integration with the audio m
arXiv:2505.09246v4 Announce Type: replace-cross Abstract: In many real-world settings, machine learning models and interactive systems have access to both structured knowledge, e.g., knowledge graphs
arXiv:2504.07738v3 Announce Type: replace Abstract: In this document, we discuss a multi-step approach to automated construction of a knowledge graph, for structuring and representing domain-specific
arXiv:2605.14221v1 Announce Type: new Abstract: Precise segmentation of brain structures in magnetic resonance imaging (MRI) is essential for reliable neuroimaging analysis, yet voxel-wise deep models
arXiv:2603.14851v3 Announce Type: replace Abstract: Integrating vision-language models (VLMs) into end-to-end (E2E) autonomous driving (AD) systems has shown promise in improving scene understanding.
arXiv:2605.15082v1 Announce Type: cross Abstract: We study a prototypical situation when a learned predictor can discover useful low-dimensional structure in data, while using fewer samples than are n
arXiv:2508.11845v3 Announce Type: replace-cross Abstract: Bioacoustics, the study of sounds produced by living organisms, plays a vital role in conservation, biodiversity monitoring, and behavioral st
b9159 is a release of llama.cpp published on May 14, 2026 . llama.cpp is a C/C++ implementation of large language model inference that enables efficient LLM execution on consumer hardware with minimal
Release b9161 of llama.cpp includes enhanced regex handling for Qwen3.5 tokenizer, adding a custom unicode handler to prevent stack overflows on long inputs . The release also adds SYCL Level Zero SDK
b9163 is a llama.cpp release that adds a custom Unicode regex handler for Qwen3.5's tokenizer to prevent stack overflows on long inputs . The release also includes improvements to SYCL memory manageme
Release b9165 fixes a transform issue with the top entry in the release archive . The release includes pre-built binaries for multiple platforms including macOS, Linux, Android, and Windows with vario
Release b9169 of llama.cpp includes updates to multi-token multimodal decoding (mtmd) functionality, adding chunks and fixing preprocessing for Qwen3A models . The changes include attention mask imple
b9172 is a release of llama.cpp that includes binaries for macOS, Linux, Android, Windows, and openEuler platforms with support for various hardware configurations including CPU, Vulkan, CUDA, ROCm, O
This article is the second installment in a series exploring Lakebase, Databricks' data management solution, providing behind-the-scenes insights into its architecture, capabilities, or integration wi
arXiv:2605.14054v1 Announce Type: new Abstract: Achieving robust perception-reasoning synergy is a central goal for advanced Vision-Language Models (VLMs). Recent advancements have pursued this goal v
arXiv:2605.14883v1 Announce Type: cross Abstract: Mild traumatic brain injury (mTBI) is a prevalent condition that remains difficult to diagnose in its early stages. Oculomotor dysfunction is a well-e
arXiv:2605.14146v1 Announce Type: new Abstract: bde is a user-friendly Python package for Bayesian Deep Ensembles with a particular focus on tabular data. Built on an efficient JAX implementation of t
arXiv:2605.14438v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures enhance the efficiency of large language models by activating only a subset of experts per token. However, standa
Beau Rothrock had been at @AngelList for two months when he walked into a Redshift-to-Snowflake migration in deep trouble, already two months behind schedule. He had a 5-week window to migrate all 14,
arXiv:2605.14417v1 Announce Type: cross Abstract: Natural language is an intuitive interface for humanoid robots, yet streaming whole-body control requires control representations that are executable
arXiv:2605.14106v1 Announce Type: new Abstract: We investigate whether behavior cloning is sufficient to produce active perception in a structured object-finding task. A low-cost robot arm equipped wi
arXiv:2605.14944v1 Announce Type: new Abstract: With the growth of the construction industry and the global shortage of skilled labor, the automation of crane control has become increasingly important
arXiv:2602.19532v2 Announce Type: replace Abstract: Real-world tasks involve nuanced combinations of goal and safety specifications. In high dimensions, the challenge is exacerbated: formal automata b
Beware the empathy exploit. Empathy is good and right when thought through (deep), but can be deadly to civilization when simply stimulus-response (shallow). For example, releasing a repeat violent of
arXiv:2605.14791v1 Announce Type: cross Abstract: Recent advances in artificial intelligence (AI) agents are pushing AI beyond tools toward autonomous scientific discovery. We discuss two complementar
arXiv:2605.14311v1 Announce Type: cross Abstract: Test-Time Scaling (TTS), which samples multiple candidate actions and ranks them via a Critic Model, has emerged as a promising paradigm for generalis
arXiv:2603.28205v2 Announce Type: replace Abstract: Aspect-Based Sentiment Analysis (ABSA) faces critical challenges due to representation entanglement and false-negative collisions in real-valued emb
// Beyond Individual Intelligence // One of the more useful multi-agent surveys I've read this year. 200+ papers mapped along three axes: collaboration mechanisms, failure attribution, and self-evolut
arXiv:2605.14892v1 Announce Type: new Abstract: LLM-based autonomous agents have demonstrated strong capabilities in reasoning, planning, and tool use, yet remain limited when tasks require sustained
arXiv:2605.14654v1 Announce Type: new Abstract: Self-supervised pre-training methods in medical imaging typically treat each individual as an isolated instance, learning representations through augmen
arXiv:2605.13935v1 Announce Type: cross Abstract: Diffusion language models are a promising alternative to autoregressive models, yet post-training methods for them largely adapt reward-maximizing obj
arXiv:2510.02837v2 Announce Type: replace Abstract: Although recent tool-augmented benchmarks involve complex requests, evaluation remains limited to answer matching, neglecting critical trajectory as
arXiv:2605.14773v1 Announce Type: cross Abstract: Data selection accelerates training by identifying representative training data while preserving model performance. However, existing methods mainly f
arXiv:2605.14886v1 Announce Type: new Abstract: Electrocardiogram (ECG) monitoring in Internet of Medical Things (IoMT) networks is constrained by strict data-sharing regulations and privacy concerns.
Big move from arXiv: a one-year ban for authors who submit AI-generated content without proper checking. This is not about banning AI from academia. AI can be extremely useful. It can help us write be
Amy Thomson / Bloomberg: Bill Ackman says his fund has taken a new stake in Microsoft after the company's recent share price decline; Ackman says investors have underestimated Microsoft — Bill Ackman