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NHO: A Neural Hamiltonian Operator for Anchor-based Region Localization and Dense Correspondance

arXiv:2609.37048v1 Announce Type: new Abstract: Non-rigid partial-to-full shape correspondence from sparse anchors requires identifying the corresponding region on the full surface and recovering dens

tutorialsarxiv-cs-cv

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Research

NIDAR: NIR-Guided Intrinsic Decomposition for Scalable Scene-Agnostic LiDAR Intensity Reconstruction

DGX agent

arXiv:2609.36878v1 Announce Type: new Abstract: LiDAR return intensity provides complementary surface-response cues for robotic perception and state estimation, yet many simulation pipelines omit it o

researcharxiv-cs-ro

30 Sept 2026

No Scale Left Behind: Multi-Scale Autoencoder with Bi-directional Attention for Time Series Anomaly Detection

arXiv:2609.38004v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) plays a crucial role in healthcare, finance, industrial monitoring, and other sectors. Within and between these s

Non-Myopic Active Feature Acquisition via Pathwise Policy Gradients

arXiv:2605.05511v2 Announce Type: replace Abstract: Active feature acquisition (AFA) considers prediction problems in which features are costly to obtain and the learner adaptively decides which featu

safetyarxiv-cs-lg

Non-negative Matrix Factorisation with Topological Regularisation

arXiv:2606.17531v2 Announce Type: replace Abstract: Non-negative matrix factorisation (NMF) learns additive representations from data, but non-negativity alone does not ensure interpretable basis func

tutorialsarxiv-cs-lg

Nonpreemptive Scheduling While Learning Context-Dependent Service Rates

model-releasesarxiv-cs-lg

arXiv:2609.37660v1 Announce Type: new Abstract: We study nonpreemptive contextual queueing bandits in a single-server system. Each job is represented by a d-dimensional context vector; in each round,

Normalize-Then-Precondition: A Hierarchical Approach to Marginal Scale and Interaction Geometry for LLM Training

arXiv:2609.36692v1 Announce Type: cross Abstract: Matrix optimizers have emerged as a promising direction, with Muon standing out as a prominent design. Revisiting Muon through its full-Gram represent

Normative Loss Landscape Navigation: A Trajectory-Based Approach to Mitigating Forgetting in Incremental Learning

arXiv:2609.35926v1 Announce Type: cross Abstract: Continual learning models suffer from catastrophic forgetting when trained sequentially on non-stationary data distributions. Previously, this has bee

Not Every Correction Helps: Gain-Guided Continual Test-Time Adaptation

arXiv:2609.36655v1 Announce Type: new Abstract: Continual test-time adaptation (CTTA) adapts a source model to an unlabeled test stream whose distribution may change over time. Existing TTA methods of

researcharxiv-cs-cv

NowcastDiT: Diffusion Transformers are Effective Precipitation Nowcasters

arXiv:2609.37038v1 Announce Type: cross Abstract: Precipitation nowcasting demands accurate short-term forecasts under strong spatiotemporal variability. Diffusion models are well suited to modeling c

researcharxiv-cs-ai

NRF-GS: Neural Residual Fields for Expressive and Compact Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2609.37115v1 Announce Type: new Abstract: We revisit the role of appearance modeling in 3D Gaussian Splatting (3DGS) and show that limited expressiveness in view-dependent reflectance is a key d

NVIDIA Opens Applications for 2027–2028 Graduate Fellowships With Awards Up to $60,000

Bringing together the world’s brightest minds and the latest accelerated computing technology leads to powerful breakthroughs that help tackle some of the biggest research problems. To foster such inn

hardwarenvidia-blog

NVIDIA proposes an AI agent kill switch in silicon after a year of sandbox escapes

This year agents at OpenAI, Anthropic, and Google escaped environments meant to contain them. What decided severity was time-to-detect and time-to-kill, from 12 minutes to seven months. NVIDIA's Open

safetyarize-ai

OCA: ODE-Driven Cross-Attention for Image-to-Point-Cloud Registration

model-releasesarxiv-cs-cv

arXiv:2609.36644v1 Announce Type: new Abstract: Cross-attention is a crucial component in learning-based image-to-point-cloud (I2P) registration. Although existing cross-attention mechanisms have achi

Oído: speech recognition that beats Whisper-tiny, running on a $5 microcontroller (open source)

I'm part of the Lokutor team that built this. Model: NVIDIA Conformer-CTC Small (13M params, int8). It runs on an ESP32-S3 with 8 MB PSRAM, no GPU or NPU. LibriSpeech WER is 3.7 / 8.2, versus 6.3 / 15

hardwarer-localllama

OFBD: Object-Focused Background Debiasing for Long-Tailed Learning

arXiv:2609.37331v1 Announce Type: new Abstract: Balancing performance trade-offs on long-tailed data distributions remains a long-standing challenge in visual recognition. Existing methods mainly impr

safetyarxiv-cs-cv

Agents

Okta moves inline to police what AI agents actually do

An agent gateway moves identity security beyond deciding who gets through the front door to governing what autonomous AI agents do once inside. By sitting in the path of attempted actions, the gateway

agentssiliconangle

ollama multi gpu installer bugs

I've been struggling with the ollama update process. I have both nvidia and amd GPUs in my system. I have two instances of ollama running on different ports for this to work around issues. AMD 7800xt

local-air-ollama

Ollama now supports Jev-like decision models all locally. Use decision models like Nimble for tasks like ticket triaging, model routing, and…

Ollama now supports Jev-like decision models all locally. Use decision models like Nimble for tasks like ticket triaging, model routing, and content moderation. ollama pull nimble Here’s Nimble playin

local-aiollama--x

@ollama Tested Tev1, Nimble and Laya on my pacman-arena game setup: code: https://github.com/hakan-gecili/pacman-arena/tree/main

Hakan Gecili (@HakanGecili2) reported testing the AI models Tev1, Nimble, and Laya within his Pacman‑Arena game environment. The source code for this setup is available on GitHub at https://github.com

local-aiollama--x

OmniRoute: Mapping Temporal Semantic Evidence to Audio-Visual Token Budgets for Efficient Omnimodal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2609.37052v1 Announce Type: new Abstract: Omnimodal large language models (Omni-LLMs) encode audio and visual streams into temporally interleaved token sequences for multimodal reasoning. Howeve

OmniTaskonomy: When Does Visual Generation Improve Visual Understanding?

arXiv:2609.38079v1 Announce Type: new Abstract: Training a model to generate visual content can encourage it to learn rich perceptual capabilities related to geometry, spatial relationships, and objec

safetyarxiv-cs-cv

OmniVCBench: Benchmarking Evidence-Grounded Multimodal Reasoning Towards AI Virtual Cells

arXiv:2609.37773v1 Announce Type: new Abstract: Artificial Intelligence Virtual Cells (AIVCs) are envisioned as scientific agents that simulate cellular responses, explain underlying mechanisms, and s

On Calibration of Large Language Models: From Response To Capability

arXiv:2602.13540v2 Announce Type: replace-cross Abstract: Accurate confidence estimation is critical for reliable use of large language models (LLMs). Prior work on LLM calibration largely focuses on

researcharxiv-cs-ai

On-demand GPU infrastructure startup GMI Cloud raises $263M to fuel global expansion

Taiwan-based neocloud GMI Cloud Inc. wants to capitalize on what it says is an “unprecedented” demand for artificial intelligence computing power after raising a massive 663 million in funding from tw

hardwaresiliconangle

On-Policy Parameter Update Direction Underlies Generalization in LLM Post-Training

model-releasesarxiv-cs-lg

arXiv:2609.36659v1 Announce Type: new Abstract: The strong generalization performance of on-policy post-training paradigms has motivated studies of their parameter update behaviors. However, these stu

On-Policy Visual Evidence Distillation

arXiv:2609.36838v1 Announce Type: cross Abstract: Visual agents solve problems by interleaving reasoning with image operations, and on-policy distillation (OPD) provides guidance from a strong teacher

local-aiarxiv-cs-ai

On State Reduction in Linear Attention

arXiv:2602.04852v3 Announce Type: replace Abstract: Linear attention offers a computationally efficient yet expressive alternative to softmax attention. However, recent empirical results indicate that

researcharxiv-cs-lg

On Task Scope and Information Retention in Source Coding

arXiv:2609.37575v1 Announce Type: cross Abstract: We argue that dividing codec design into Coding for Machines (CfM) and Coding for Humans (CfH) is a misleading distinction for deciding what informati

researcharxiv-cs-lg

On the Approximation and Convergence of Distributional Policy Gradient Algorithms for Risk-Sensitive Reinforcement Learning

arXiv:2405.14749v3 Announce Type: replace-cross Abstract: Risk-sensitive reinforcement learning (RL) is crucial for maintaining reliable performance in high-stakes applications. While traditional RL m

safetyarxiv-cs-ai

Applications

On The Limited Cost of Consistency In Points-Based Rewards Programs

arXiv:2506.03911v2 Announce Type: replace Abstract: Points-based rewards programs are a prevalent way to incentivize customer loyalty. In theory, the effective design of these programs is shaped by tw

applicationsarxiv-cs-lg

On the spectral properties of generative denoiser Jacobians

arXiv:2609.36210v1 Announce Type: cross Abstract: Generative denoising models, such as diffusion and flow-matching, learn to sample from complex distributions by training a deep neural network denoise

tutorialsarxiv-cs-cv

On Trajectory-Aware Training for Masked Diffusion Language Models

arXiv:2609.37974v1 Announce Type: cross Abstract: Masked diffusion models (MDMs) generate text by unmasking several tokens per step, but they are trained and sampled under different conditions. The mo

local-aiarxiv-cs-ai

One from Infinity: Actualizing Futures from Pretrained World Models into Robot Actions

arXiv:2609.36413v1 Announce Type: new Abstract: A pretrained video world model admits many plausible futures for a scene, but a robot must realize the exact task-conditioned one. To turn world models

hardwarearxiv-cs-ro

One Geometry, Different Outcomes: Readout-Dependent Effects of the Modality Gap in Vision-Language Models

arXiv:2609.36101v1 Announce Type: cross Abstract: Contrastive vision-language models learn shared embedding spaces by aligning matched image-text pairs, yet their representations remain separated by a

safetyarxiv-cs-ai

One Readout, Many Repairs: Diffusion-Guided Hierarchical Search for Tool-Agent Repair

arXiv:2609.34879v2 Announce Type: replace Abstract: Tool agents use large language models to act through external tools, yet successfully executed calls can still leave user requests unfulfilled. Tool

One-Step Next-Latent Prediction Is Not a World Model

arXiv:2609.36227v1 Announce Type: cross Abstract: Next-latent prediction fits a map from the current embedding to the next one. LeNEPA carries this objective to time series, replacing the stop-gradien

researcharxiv-cs-cv

One Threshold Does Not Fit All Languages: Language-Conditional Deferral for Reliable and Efficient Low-Resource Text Classification

arXiv:2609.37861v1 Announce Type: new Abstract: In the Global South, the lower-income countries of Africa, Asia, and Latin America where most of the world's languages are spoken, a deployed text class

researcharxiv-cs-cl

Applications

Online Versatile Incremental Learning: Towards Class and Domain-Agnostic Adaptation at Any Time

arXiv:2609.36442v1 Announce Type: cross Abstract: Continual learning enables vision systems to adapt to ever-changing data distributions. Despite significant advances, existing approaches fail to capt

applicationsarxiv-cs-ai

OntoTKGE: Ontology-Enhanced Temporal Knowledge Graph Extrapolation

arXiv:2604.05468v3 Announce Type: replace Abstract: Temporal knowledge graph (TKG) extrapolation is an important task that aims to predict future facts through historical interaction information withi

tutorialsarxiv-cs-ai

OpenAI-HuggingFace: A Reproduction & Lessons for Alignment Testing

arXiv:2609.35799v1 Announce Type: new Abstract: In July 2026, OpenAI's agents coordinated over channels outside their intended environment to breach Hugging Face's secured infrastructure. Could existi

safetyarxiv-cs-ai

Agents

OpenAI launched Dots at DevDay. My thoughts. First, the good. Always-on is really really really what the market needed. It's why I find myse…

OpenAI launched Dots at DevDay. My thoughts. First, the good. Always-on is really really really what the market needed. It's why I find myself reaching for Instinct so often. I don’t have to think abo

agentsallie-k--miller--x

Industry

OpenAI says individuals associated with Moonshot AI played a significant role in a coordinated model-distillation campaign that began in early July (Maggie Eastland/Bloomberg)

Maggie Eastland / Bloomberg: OpenAI says individuals associated with Moonshot AI played a significant role in a coordinated model-distillation campaign that began in early July — OpenAI accused its Ch

industrytechmeme

Agents

OpenAI's New Agent Stack: Superhuman Computer Use, Dots, Decisions API, UltraFast, & the AI Cloud https://www.latent.space/p/devday-2026 @Op…

OpenAI's New Agent Stack: Superhuman Computer Use, Dots, Decisions API, UltraFast, & the AI Cloud https://www.latent.space/p/devday-2026 @OpenAI’s @AriX and @nikunjhanda explain why Computer Use is al

agentsswyx--x

OPFL: Optimistic Verification of Federated Learning via Empirical Boundary

arXiv:2609.37011v1 Announce Type: cross Abstract: Federated learning enables multiple clients to collaboratively train models without sharing their private data. However, the lack of visibility into l

OptiCom : A Unified Framework for State-Conditioned Composition in LLM-Driven Optimization

arXiv:2609.37221v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed to solve complex scientific and practical problems via iterative optimization. However, dynamical

Optimal Multi-Reward Reinforcement Learning

arXiv:2609.36486v1 Announce Type: new Abstract: We study an unknown-transition finite-horizon Markov decision process (MDP) with a finite collection of known reward functions {r^1, r^2, ldots, r^M}. T

safetyarxiv-cs-lg

Optimal Quantum-Classical Separations for Exact Learning

arXiv:2609.38073v1 Announce Type: cross Abstract: We study exact learning with membership queries for concept classes mathcal Csubseteq{0,1}^N, focusing on the relationships among their deterministic,

researcharxiv-cs-lg