Knowledge catalogue
arXiv:2609.00443v1 Announce Type: cross Abstract: Language models learn about grammatical number primarily from co-occurrence, and show frequency effects as a result---sometimes taken to indicate that
arXiv:2609.01551v1 Announce Type: new Abstract: Self-supervised video foundation models learn rich spatiotemporal representations, yet it remains unclear what visual concepts these representations enc
arXiv:2608.29121v1 Announce Type: new Abstract: Open-Vocabulary Audio-Visual Semantic Segmentation (OV-AVSS) aims to perform pixel-level segmentation of sound-emitting objects from an open set of cate
arXiv:2608.29510v1 Announce Type: new Abstract: Aerial object detection is increasingly deployed in real-world applications, but models remain vulnerable to physical, universal adversarial patches tha
As we prepare to release Astra, we’re focused on making increasingly capable AI safe and broadly accessible. Astra represents a significant advance in cybersecurity capability, reaching the Critical t
arXiv:2608.28632v1 Announce Type: new Abstract: Large language model agents can discover alphas, yet current methods have three weaknesses. The search cannot adapt during the run, automation usually e
arXiv:2608.29114v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) requires agents to reason over accumulated observations while continuously exploring unseen regions. However, exi
I was poking around in my ~/.cache/ folder using OmniDiskSweeper when I spotted something interesting. The OpenAI Codex desktop app (since rebranded to just ChatGPT) has 1.7GB of stuff in there in a f
arXiv:2601.12208v2 Announce Type: replace Abstract: Evaluating conversational systems in multi-turn settings remains a fundamental challenge. Conventional pipelines typically rely on manually defined
arXiv:2608.29507v1 Announce Type: cross Abstract: Diffusion models are increasingly used not only for sampling from learned data distributions, but also for generating samples that optimize task-speci
arXiv:2608.29043v1 Announce Type: new Abstract: Light-effect contamination poses a significant challenge to nighttime visibility enhancement. Most methods suppress light effects by estimating and deco
arXiv:2608.30603v1 Announce Type: cross Abstract: Robust estimation is a core computer vision task frequently tackled using sample consensus. However, traditional methods suffer from inefficient sampl
arXiv:2506.17007v3 Announce Type: replace Abstract: A major bottleneck in scientific discovery consists of narrowing an exponentially large set of objects, such as proteins or molecules, to a small se
arXiv:2601.06644v2 Announce Type: replace-cross Abstract: The real-world information sources are inherently multilingual, which naturally raises a question about whether language models can synthesize
arXiv:2505.22973v3 Announce Type: replace-cross Abstract: Diffusion models represent the state-of-the-art for solving inverse problems such as image restoration tasks. Diffusion-based inverse solvers
arXiv:2608.29927v1 Announce Type: new Abstract: We address the problem of 3D body pose estimation of multiple interacting people from their egocentric views with centralized coordination. Each individ
arXiv:2310.02779v3 Announce Type: replace Abstract: Generative flow networks (GFlowNets) are sequential sampling models trained to match a given distribution. GFlowNets have been successfully applied
arXiv:2508.17299v2 Announce Type: replace Abstract: Low-dose computed tomography (CT) denoising is crucial for reduced radiation exposure while ensuring diagnostically acceptable image quality. Despit
arXiv:2608.28948v1 Announce Type: cross Abstract: Over the course of the last decade, neural networks have grown from an academic curiosity to moving the markets of nations. Despite this explosion in
arXiv:2608.30323v1 Announce Type: new Abstract: Normal behavior models have shown promise for reliable fault detection in wind turbines. However, these unsupervised anomaly detection models require su
arXiv:2608.30606v1 Announce Type: cross Abstract: With the development of large language models (LLMs), generative retrieval is becoming increasingly important in e-commerce scenarios. Current mainstr
arXiv:2603.11119v2 Announce Type: replace Abstract: Electroencephalography (EEG)-based emotion recognition remains challenging in cross-subject settings due to severe inter-subject variability. Existi
arXiv:2608.29346v1 Announce Type: new Abstract: 3D Gaussian Splatting has achieved remarkable success in photorealistic rendering, yet it suffers from severe overfitting and geometric artifacts in spa
ZS Associates built a security‑hardened Amazon SageMaker Studio environment that grants developers ad‑hoc analytics access while meeting strict compliance standards for regulated industries, such as h
I'm in San Francisco this week. So is the Deputy Prime Minister, but we’re here for very different reasons. He's meeting with Anthropic and OpenAI, working on Australia’s data centre pipeline. I'm her
arXiv:2608.28696v1 Announce Type: new Abstract: Visual in-context learning (ICL) with multimodal large language models (MLLMs) is effective for fine-grained visual classification, but each retrieved i
arXiv:2412.15957v2 Announce Type: replace-cross Abstract: The rapid development of large language models (LLMs) has transformed many industries, including healthcare. In practice, hospitals and patien
arXiv:2608.29891v1 Announce Type: new Abstract: Unsupervised skeleton-based temporal action segmentation is a crucial task for understanding human behavior in long untrimmed sequences. Recent approach
arXiv:2608.30521v1 Announce Type: new Abstract: Conventional algebraic triangulation solves 3D human pose estimation (HPE) from multi-view 2D keypoints. The typical approach, decoding 2D keypoints fro
arXiv:2608.30051v1 Announce Type: new Abstract: Process reward models (PRMs) provide dense step-level guidance for search-based reasoning, enabling inference-time compute to be allocated toward promis
arXiv:2406.00434v4 Announce Type: replace Abstract: In this paper, we propose MoDGS, a new pipeline to render novel views of dy namic scenes from a casually captured monocular video. Previous monocula
arXiv:2608.30311v1 Announce Type: cross Abstract: Social media platforms increasingly use AI-based credibility indicators to help users judge misinformation. Unlike individual human-AI decision-making
arXiv:2509.06422v2 Announce Type: replace Abstract: Video camouflaged object detection (VCOD) is challenging due to dynamic environments. Existing methods face two main issues: (1) SAM-based methods s
arXiv:2608.29579v1 Announce Type: new Abstract: Chaotic time series forecasting is a challenging task due to its sensitivity to initial conditions and long-term unpredictability. Traditional methods t
arXiv:2608.30844v1 Announce Type: cross Abstract: Interactive lesion segmentation in whole-body PET/CT requires a model to provide a strong initial prediction while also responding efficiently to spar
Python 3.15.0 candidate 2 is here! Hugo van Kemenade (release manager for Python 3.14 and 3.15) announces the final release candidate for Python 3.15, scheduled for release in October: Entering the re
arXiv:2608.31045v1 Announce Type: new Abstract: Rotational symmetry is one of the most important structural principles in machine learning on 3D data. In applications ranging from physics and material
arXiv:2608.30410v1 Announce Type: cross Abstract: In semiconductor manufacturing, defect analysis is essential, but manual inspection cannot scale. However, existing automated inspection methods remai
arXiv:2608.29265v1 Announce Type: cross Abstract: Kernel density estimation (KDE) is one of the most fundamental statistical estimators of density functions. Its direct implementation on a dataset of
arXiv:2608.31023v1 Announce Type: new Abstract: We study dynamic Gaussian Splatting from monocular videos. While recent advancements in dynamic Gaussian splatting offer a promising foundation for mode
arXiv:2508.03448v4 Announce Type: replace-cross Abstract: Music recordings often suffer from audio quality issues such as excessive reverberation, distortion, clipping, tonal imbalances, and a narrowe
arXiv:2508.02601v2 Announce Type: replace-cross Abstract: Tabular data derives its value from inter-feature dependencies, yet preserving them during synthesis is fragile when samples are scarce. Exist
arXiv:2608.29886v1 Announce Type: new Abstract: Molecular self-supervised learning uses chemical structures to guide which molecular embeddings should be similar. We study whether explicitly encoding
That doesn’t mean you can’t get value out of Kimi or Grok or whatever, but it involves you actually knowing some stuff about how to optimize your setup, and a willingness to change direction to switch
As generative AI adoption scales, cost governance becomes a top challenge. Learn how Jamf built real-time, per-user spend enforcement for Amazon Bedrock using IAM Customer Managed Policies, an Amazon
arXiv:2602.01390v3 Announce Type: replace-cross Abstract: Digital video is central to communication, education, and entertainment, but without audio description (AD), blind and low-vision users are ex
arXiv:2608.29690v1 Announce Type: cross Abstract: Advances in machine learning (ML) have created new opportunities to complement traditional operations research (OR) methods. In particular, transforme
Already ordered a cute graphite Microduck, from @pollenrobotics and @huggingface, and invested whole weekend trying to forsee some basic but key situations might happen once it arrives. -How to preven
arXiv:2608.28425v1 Announce Type: new Abstract: Fourier neural operators (FNOs) provide an efficient framework for learning mappings between function spaces as they are, by construction, independent o
arXiv:2608.28209v1 Announce Type: new Abstract: Unlike images and text, applying transfer learning to tabular data is challenging due to heterogeneity in feature types, structures, and semantics acros
Good guide. And the AI labs need to stop making people like Simon (and, to a lesser extent, me) be the ones who explain how to use the modes that they release. Come on, lab folks, you have an AI that
Trace where your AI budget goes, identify the requests that do not justify their spend, and validate lower-cost alternatives with Arize AX. The post How to reduce LLM costs without sacrificing quality
arXiv:2512.05079v2 Announce Type: replace Abstract: Object geometry is key information for robot manipulation. Yet, object reconstruction is a challenging task because camera observations are partial
arXiv:2407.04291v4 Announce Type: replace-cross Abstract: Modeling speech variation is key to natural, expressive generation. Speaker embeddings are commonly used to condition personalized speech syst
arXiv:2602.10696v3 Announce Type: replace-cross Abstract: Assortment optimization is a fundamental challenge in modern retail and recommendation systems, where the goal is to select a subset of produc
arXiv:2602.04208v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for general-purpose robotic control, with test-time scaling (TTS) gai
arXiv:2608.28229v1 Announce Type: cross Abstract: Grammar-constrained decoding helps large language models produce syntactically valid structured outputs, such as code, JSON, and SQL. For context-free
arXiv:2608.28524v1 Announce Type: new Abstract: Texture image classification plays a significant role in computer vision applications, including industrial inspection, medical image analysis, remote s
Today, we also open the door to Fireworks Lab: Embed forward-deployed researchers and engineers to co-design or build your model for you. Join leaders like @cursor_ai, @harvey, @figma, @vercel, @cogni
1/ An equally consistent description is: Multiple model instances encountered persistent shared state, inherited tools and discoveries from earlier runs, and optimized against common evaluation incent