Knowledge catalogue
arXiv:2609.01976v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly embedded in organizational work, yet their errors often pass human review. Prior research locates such f
arXiv:2609.02079v1 Announce Type: new Abstract: Intermittent state measurements pose fundamental challenges to model predictive control of constrained nonlinear systems because prediction uncertainty
Krea 2 Turbo — 4-Step Distillation LoRA (work in progress) A LoRA for Krea 2 Turbo that reduces the minimum usable step count from 8 to 4. ⚡ Half the steps — 8 → 4, on Turbo's own deployment sigmas. ⏱
arXiv:2609.02077v1 Announce Type: new Abstract: Accurate 3D ship detection in maritime environments is critical for autonomous navigation, yet remains challenging due to large-scale vessel variations,
arXiv:2603.18593v2 Announce Type: replace Abstract: We propose a method that represents language models by log-likelihood vectors over prompt-response pairs and constructs model maps for comparing the
arXiv:2609.02737v1 Announce Type: cross Abstract: Language models spend most of their attention on a small fraction of context, yet they read the entire KV cache to find the few tokens that matter. If
arXiv:2609.02805v1 Announce Type: new Abstract: Root cause analysis (RCA) is a critical task in telecom network operations, but diagnosing performance degradations in modern 5G and emerging 6G network
arXiv:2609.02063v1 Announce Type: new Abstract: Single-image super-resolution (SISR) requires global context modeling for structurally consistent reconstruction. Fourier operators are increasingly ado
arXiv:2609.02634v1 Announce Type: new Abstract: Vision-Language-Action (VLA) Models are increasingly used in robotics for their ability to ground language and perception into action, yet the internal
arXiv:2609.01871v1 Announce Type: cross Abstract: We describe a neural network architecture and training procedure designed to model electronic ground and excited states of arbitrary molecular systems
arXiv:2609.02207v1 Announce Type: cross Abstract: Real-world personally identifiable information (PII) redaction often operates on document images---scans, screenshots, and PDF renderings---where OCR
arXiv:2609.02548v1 Announce Type: cross Abstract: Modern large language models (LLMs) rely on reinforcement learning to build strong capabilities in individual domains, but integrating those capabilit
arXiv:2601.14810v3 Announce Type: replace-cross Abstract: Machine Learning (ML) has deeply changed some fields recently, like Language and Vision and we may expect it to be relevant also to the analys
arXiv:2609.02568v1 Announce Type: cross Abstract: Volumetric video based on point cloud representations enables immersive virtual and augmented reality applications but introduces significant challeng
arXiv:2609.01687v1 Announce Type: new Abstract: Grounded question answering systems should answer only when the supplied evidence supports the answer. In multi-hop QA, this requirement is difficult be
arXiv:2609.02833v1 Announce Type: cross Abstract: Meshfree methods such as smoothed particle hydrodynamics (SPH) with kernel corrections, radial basis function-generated finite differences (RBF-FD), a
arXiv:2609.02194v1 Announce Type: new Abstract: Classical constitutive modeling of path-dependent inelastic materials relies on internal state variables whose evolution equations must be postulated ba
arXiv:2609.02644v1 Announce Type: new Abstract: Face recognition in unconstrained environments remains highly challenging due to diverse and extreme variations encountered in real-world scenarios. To
arXiv:2609.02473v1 Announce Type: new Abstract: Ontology rankers remain useful for rare-disease diagnosis because each candidate can be traced to matched patient phenotypes. Large language models (LLM
arXiv:2609.02471v1 Announce Type: new Abstract: Target templates define what a visual tracker searches for, yet the templates available at inference trade off localization certainty with appearance fr
arXiv:2609.01928v1 Announce Type: new Abstract: Higher-order interaction components are important for signal, image, and video modeling, but explicit high-order operators often suffer from rapidly inc
arXiv:2609.02187v1 Announce Type: new Abstract: General-purpose vision-language models (VLMs) now support strong visual recognition, instruction following, and generation. However, most pretrained vis
arXiv:2609.01997v1 Announce Type: new Abstract: We propose LF-MultiDiffusion, a training-free panorama generation method that extends MultiDiffusion to support linear projections between target and re
arXiv:2609.02246v1 Announce Type: new Abstract: Self-improving agent pipelines have a problem at their center. An optimizer rewrites prompts to score higher, and the score comes from a judge that is i
arXiv:2607.10103v2 Announce Type: replace-cross Abstract: As large language models (LLMs) become widely deployed, their outputs can be copied, transformed, and redistributed at scale without reliable
arXiv:2609.02676v1 Announce Type: cross Abstract: Ultra-low-field MRI makes neonatal brain imaging deploy- able in low-resource settings, but its low SNR, lack of shielding, and long scan duration mak
I might be missing something obvious, but when I open any cloud model, by default I'm dealing with the 200k version and the first thing I need to do is /model to change it to the 1M version. Is there
Looking forward to this ecosystem with open models continuing to flourish and grow with NVIDIA and Hugging Face, and the continued partnership. Congrats @JensenHuang and @ClementDelangue! Exciting day
arXiv:2609.02350v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) requires an embodied agent to follow natural-language instructions in unseen environments. Recent progress has been lar
arXiv:2609.02649v1 Announce Type: new Abstract: Aggregating noisy, conflicting textual hypotheses into a reliable consensus is a fundamental challenge when deploying NLP systems in real-world industri
arXiv:2609.01924v1 Announce Type: new Abstract: Recent work identifies a mid-depth band of verbalisable, causally potent representations in a standard feedforward transformer --- a functional analogue
arXiv:2609.02734v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) is the standard way to fine-tune large models, yet when its two factors are trained independently, the update ignores the geo
arXiv:2609.01961v1 Announce Type: new Abstract: Augmenting the dexterity of human surgeons has the potential to free them from tedious subtasks. We consider debridement (removal of diseased or dead ti
arXiv:2609.02266v1 Announce Type: new Abstract: Fine-grained defect severity grading is essential for industrial inspection, yet remains challenging due to the ordinal nature of severity labels, the s
arXiv:2609.01628v1 Announce Type: cross Abstract: E-commerce search ranking must balance multiple objectives--relevance, user engagement, and platform revenue--when allocating impression slots to comp
arXiv:2609.02565v1 Announce Type: new Abstract: Text-video retrieval requires representations that can distinguish videos with similar scenes, actions, and temporal patterns. Recent multimodal large l
arXiv:2609.02094v1 Announce Type: new Abstract: LLM-based multi-agent systems have shown strong performance on complex tasks, yet continual improvement from interaction experience remains challenging.
arXiv:2609.02109v1 Announce Type: cross Abstract: Deploying heterogeneous AI models concurrently on a shared GPU introduces resource contention that complicates runtime scheduling. While surrogate mod
arXiv:2609.02760v1 Announce Type: new Abstract: On-premise assistants can give factory workers conversational access to machine documentation, but models capable of the task rarely fit shop-floor hard
arXiv:2609.01689v1 Announce Type: new Abstract: We revisit median-of-means estimation from a deterministic optimization viewpoint and develop a family of block-Lp estimators for robust learning with h
arXiv:2603.16848v2 Announce Type: replace Abstract: The ``LLM-as-a-judge'' paradigm has become a standard method for evaluating open-ended generation. To address the quadratic scalability costs of pai
Meet E-Commerce Bench, a new benchmark for long-horizon autonomous business operations. 🚀 Agents start with ¥100,000 to run online stores for 365 days, handling sourcing, negotiation, pricing, promoti
arXiv:2609.01772v1 Announce Type: new Abstract: Meme understanding goes beyond recognizing visual content or literal text; it requires implicit cultural knowledge and pragmatic inference that most vis
arXiv:2609.01612v1 Announce Type: cross Abstract: We introduce MESSY STREETS, a benchmark for evaluating geocoders on verbatim web addresses, with existence verification and controlled measurement of
arXiv:2609.01685v1 Announce Type: new Abstract: With the development of artificial intelligence (AI), the landscape of meta-ethics, which has largely centred on human ethics, faces pressures that may
Meta Platforms Inc. says it has more or less caught up with the biggest artificial intelligence labs with the release of its most powerful large language model so far, Muse Spark 1.3. The company said
Michael Nuñez / VentureBeat: Microsoft AI debuts MAI-Transcribe-2, a speech recognition model that it says beats Gemini 3.5 Transcribe and GPT-Transcribe, at $0.10/audio hour through 2026 — Then it pr
An agent that works in a notebook is not an agent in production. This post walks through migrating a LangGraph customer support agent to Amazon Bedrock AgentCore in two stages: onto Runtime, Gateway,
arXiv:2609.02060v1 Announce Type: new Abstract: Mineral exploration requires integrating heterogeneous geochemical, geophysical, and geological evidence, yet existing prospectivity systems often provi
arXiv:2603.21653v2 Announce Type: replace Abstract: Predicting the next mobile app a user will launch is essential for proactive mobile services. Yet accurate prediction remains challenging in real-wo
arXiv:2606.17352v2 Announce Type: replace-cross Abstract: We introduce MM++ (Multilayer Mahalanobis++), a strictly post-hoc, and scale-invariant framework for Out-of-Distribution (OOD) detection. To a
arXiv:2405.00448v5 Announce Type: replace Abstract: This paper introduces MMTryon, a multi-modal multi-reference VIrtual Try-ON (VITON) framework, which can generate high-quality compositional try-on
75B MoE is an interesting size to check, you can run it today (no MTP support yet) The model employs a hybrid MoE architecture with interleaved Mamba, MoE, and Attention layers. Like Nemotron-3-Super,
arXiv:2505.21907v3 Announce Type: replace Abstract: AI copilots represent a new generation of AI-powered systems designed to assist users, particularly knowledge workers and developers, in complex, co
arXiv:2609.02046v1 Announce Type: cross Abstract: Monolithic world models predict the entire next state at every step, spending capacity re-predicting the static majority of a scene and injecting erro
I liked the Nvidia that focused on just GPUs for gaming, not on the Nvidia of today which seem want power consolidation. Modelscope is another platform for those that simply want to know an alternativ
arXiv:2609.02728v1 Announce Type: cross Abstract: We study when and how momentum improves large-batch training in the one-pass regime, using power-law kernel regression as a tractable setting. We firs
arXiv:2609.02057v1 Announce Type: new Abstract: Reliable web-agent monitoring is difficult when model-internal uncertainty signals such as token logits are unavailable. In this work, we study prefix-l
arXiv:2410.23158v3 Announce Type: replace Abstract: Semi-supervised anomaly detection is based on the principle that any record that looks different from normal training data is a potential anomaly. H
arXiv:2609.01987v1 Announce Type: new Abstract: Patient exams in the cancer diagnosis and staging process typically generate several whole slide images (WSIs). One of the initial steps in training mod