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arXiv:2609.22289v1 Announce Type: new Abstract: Large-scale egocentric and whole-body human demonstrations are becoming a primary source of data for embodied intelligence. They record what people perc

tutorialsarxiv-cs-ro

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Okta adds AI agent runtime gateway, forms Blueprint Alliance with AWS and CrowdStrike

DGX agent

Identity and access management company Okta Inc. used the opening day of its Oktane conference in Las Vegas today to announce runtime enforcement and a wider kill switch for its Okta for AI Agents pla

agentssiliconangle

22 Sept 2026

Omni2Web: Benchmarking Audiovisual Website Development

model-releasesarxiv-cs-cv

arXiv:2609.23417v1 Announce Type: cross Abstract: Screen-recorded web editing requests contain weak deictic expressions such as ``this'' and ``there,'' whose referents depend on speech, cursor traject

OmniEdu: Open Foundation Models for Learning and Teaching

arXiv:2609.23088v1 Announce Type: new Abstract: Educational foundation models must solve problems, understand curriculum structure, diagnose learner difficulties, and provide appropriate instructional

On attention heads and bilinear forms

arXiv:2609.22990v1 Announce Type: new Abstract: We study the symmetric and antisymmetric parts of bilinear forms in the attention heads of trained large language models. We introduce an orthogonally i

On Emergent Capabilities and Model Merging

arXiv:2609.24504v1 Announce Type: new Abstract: Fine-tuned checkpoints and adapters now fill public repositories, and the most common operation applied to these artifacts is model merging: arithmetic

On Generalized Naive Bayes with Continuous Features

arXiv:2609.23819v1 Announce Type: cross Abstract: The Generalized Naive Bayes (GNB) model was introduced for discrete and categorical random variables as an extension of classic Naive Bayes. We now ac

On Learning Spatial Structure from Pre-Beamforming Per-Antenna Range-Doppler Radar Measurements

arXiv:2604.01921v2 Announce Type: replace Abstract: Automotive radar perception pipelines commonly construct angle-domain representations via beamforming before applying learning-based models. This wo

On Mitigation of Subliminal Learning in Large Language Models

arXiv:2609.22215v1 Announce Type: new Abstract: Knowledge distillation can transmit unintended behavioral traits from a teacher model to a student through training data that appear semantically unrela

On Policy Stochasticity in Mutual Information Optimal Control of Linear Systems

arXiv:2507.21543v3 Announce Type: replace-cross Abstract: Mutual information regularization has recently been studied in reinforcement learning (RL) as an extension of entropy regularization, in which

Agents

On the Control of Mobile Ad-Hoc Agent Deployments in Partially Observed Space

arXiv:2609.23060v1 Announce Type: new Abstract: We study the online deployment of mobile ad hoc networks in unknown orthogonal environments, formalized as the Partially Observable Cooperative Guard Ar

agentsarxiv-cs-ro

On the Efficiency-Safety Dilemma in Large Reasoning Models

arXiv:2609.23587v1 Announce Type: new Abstract: Large reasoning models (LRMs) incur high inference costs, often mitigated by efficiency techniques like quantization and pruning. However, the impact of

safetyarxiv-cs-cl

On the Information-Theoretic Limits of Latent-Space Watermarking Through Pretrained Generators

arXiv:2609.24377v1 Announce Type: cross Abstract: We study latent-space watermarking through a pretrained generator using a prescribed latent-to-output stochastic mapping, called the renderer. A water

On The Robustness-Resolution Tradeoff In Temporal Quantization Of Event Streams

arXiv:2609.22295v1 Announce Type: new Abstract: Event pipelines often discretize asynchronous timestamps before learning. This step looks harmless, but its stability depends directly on temporal resol

One Patch, Three Roles: What Is Actually Coupled in Autoregressive Time-Series Forecasting?

arXiv:2609.23686v1 Announce Type: new Abstract: Patch-based autoregressive time-series forecasting often ties input representation, learned transitions, and recursive execution to one patch length. We

One to More, More to One: Category-Aware Iterative Expert Training for Software Engineering Agents

arXiv:2609.23377v1 Announce Type: cross Abstract: Repository-level software engineering (SWE) comprises heterogeneous task categories, whose progress under pooled agentic reinforcement learning can be

safetyarxiv-cs-cl

OnlineWM: Causality-Aware Active Online Learning for Effective World Modeling

arXiv:2609.23753v1 Announce Type: new Abstract: Generative world models aim to predict future states conditioned on actions, where action controllability is fundamental for reliable dynamics modeling.

onPanda: Efficient Annotation of On-Policy Alignment Data for LLMs and Agents via Token-Level Correction

arXiv:2609.24983v1 Announce Type: new Abstract: We present onPanda, an interactive tool for efficiently annotating LLM alignment data and agent trajectories. onPanda adopts token-level correction as i

Hardware

Open-Jev Judgments on CallScreenBench: Calibrated One-Pass Scam Screening with a Small Language Model

arXiv:2609.23959v1 Announce Type: new Abstract: Screening a phone call for fraud needs a trustworthy probability after every caller turn, in milliseconds. Jev-style typed decisions promise exactly tha

hardwarearxiv-cs-cl

Open Source: Ming-Image-0.1-Design family: Ming-Image-0.1-Design, 6B & Ming-Image-0.1-Design-Layer, 6B

model-releasesr-stablediffusion

Ming-Image-0.1-Design creates complete UIs, dashboards, infographics, and posters from structured prompts of up to 8K tokens, with consistent layouts, typography, colors, and imagery. It can also nati

OpenAI launches GPT-6 Sol and Luna, saying Sol makes about half as many mistakes as GPT-5.6 Sol and Luna matches GPT-5.6 Sol's performance at ~1% of the cost (David Gewirtz/ZDNET)

David Gewirtz / ZDNET: OpenAI launches GPT-6 Sol and Luna, saying Sol makes about half as many mistakes as GPT-5.6 Sol and Luna matches GPT-5.6 Sol's performance at ~1% of the cost — GPT-6 Sol and Lun

model-releasestechmeme

OpenAI says it plans to let third-party groups conduct technical safety evaluations of its AI models during the training, evaluation, and deployment phases (Rachel Metz/Bloomberg)

Rachel Metz / Bloomberg: OpenAI says it plans to let third-party groups conduct technical safety evaluations of its AI models during the training, evaluation, and deployment phases — OpenAI plans to l

safetytechmeme

Tutorials

OpenAI wants to consult elite mathematicians about how to not fumble again

After turning a string of spectacular mathematical results into a reputational crisis, OpenAI is consulting human mathematicians to help it figure out a less disastrous path forward. On Monday, the co

tutorialsthe-verge-ai

Agents

OpenBlock: Constructive and Verified Content Generation for Adaptive Tile-Matching Games

arXiv:2609.22177v1 Announce Type: new Abstract: Tile-matching puzzle games serve hundreds of millions of players, yet the content-generation algorithms that decide which pieces to present at each turn

agentsarxiv-cs-lg

OpenFlyScan: A Quality-Guided Aerial Reconstruction System for Consumer Drones

arXiv:2609.24253v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) provides high-fidelity scenes for large-scale embodied simulation, but constructing large-scale urban assets remains cons

Opinion Leader Dynamics: How Sparse Attention Shapes Token Clustering

arXiv:2609.24202v1 Announce Type: new Abstract: Sparse attention reduces the quadratic cost of global self-attention while retaining strong empirical performance, but how its restricted interactions s

Opt2VLA: Force-Aware Vision-Language-Action for Contact-Rich Humanoid Whole-Body Manipulation

arXiv:2609.23968v1 Announce Type: new Abstract: Humanoid robots are expected to perform diverse human-level tasks in daily environments, many of which require precise regulation of interaction forces.

safetyarxiv-cs-ro

Applications

Optimal Multi-way Decision Trees for Stratified Sampling in Online Controlled Experiments

arXiv:2609.23308v1 Announce Type: new Abstract: Online controlled experiments, or A/B tests, are widely used to estimate causal effects on digital platforms. A central challenge is to improve experime

applicationsarxiv-cs-lg

Optimal No-Regret Learning for Repeated Prophet Inequality

arXiv:2609.23265v1 Announce Type: new Abstract: We study repeated prophet inequalities under prefix feedback. In each of T rounds, a learner encounters fresh values drawn independently from n boxes wi

Optimal Sample Complexity of Stable Discounted Markov Decision Processes

arXiv:2302.07477v4 Announce Type: replace Abstract: We study the optimal sample complexity of tabular reinforcement learning for infinite-horizon discounted Markov decision processes. The unrestricted

Optimal Symmetries in Binary Classification

arXiv:2408.08823v2 Announce Type: replace Abstract: We develop a theoretical foundation for designing group-equivariant neural networks that align the choice of symmetries with the underlying probabil

Optimizers for Diffusion Models: A Controlled Benchmark

arXiv:2609.23055v1 Announce Type: new Abstract: Discrete diffusion models now match autoregressive language models on several benchmarks, while the question of how best to train them has received far

Opus 5.5 is the best frontier model for parsing tables in PDFs. We ran it through ParseBench, and it scored 93.9%, a 7%+ increase over Opus …

model-releasesjerry-liu--x

Opus 5.5 is the best frontier model for parsing tables in PDFs. We ran it through ParseBench, and it scored 93.9%, a 7%+ increase over Opus 5, and beating Fable/Gemini/Astra. It's comparable to LlamaP

Opus 5.5 made me curse at Claude less, which is an unfortunate benchmark to now be using but a win.

model-releasesallie-k--miller--x

On 22 September 2026, Allie K. Miller posted on Twitter that the Opus 5.5 model led her to curse at Claude less frequently. She notes that while reducing profanity toward another AI is an undesirable

ORDER: A Fictitious-World Benchmark for Domain-Adaptive Embodied AI

model-releasesarxiv-cs-ro

arXiv:2609.22285v1 Announce Type: new Abstract: Adapting language models to new domains via continual pre-training raises a basic evaluation problem: if the training corpus overlaps with what the mode

Orientation-Aware Control and Trajectory Design for Aerial RIS-Assisted Wireless Communications

arXiv:2609.23157v1 Announce Type: cross Abstract: Aerial Reconfigurable Intelligent Surfaces (ARISs) can enhance wireless connectivity in obstructed environments by combining reconfigurable metasurfac

researcharxiv-cs-ro

Local Ai

ORION-CMR: On-scanner Reporting with Integrated Foundation Model for End-to-End Cardiac MRI Analysis and Interpretation

arXiv:2609.23950v1 Announce Type: cross Abstract: Cardiovascular magnetic resonance (CMR) provides comprehensive cardiac assessment but remains underutilized because of the complexity of acquisition,

local-aiarxiv-cs-cv

OSCAR: Order-aware Scoring and Calibration for AI Rankings

arXiv:2609.24128v1 Announce Type: cross Abstract: Judge-specific sensitivity is useful for aggregating pairwise LLM evaluations, but its interpretation depends on which systematic presentation effects

OSWorld-Pro: Process-based Evaluation for Computer Use Agents

arXiv:2609.24890v1 Announce Type: new Abstract: Evaluation of Computer-Use Agents (CUAs) is often limited to the final deliverables they create (at the end of hundreds of steps) and assessed with func

Over the last few hours, some requests to the deepseek-v4.1-flash model on Ollama were charged at an incorrect rate, leading to higher usage…

Over the last few hours, some requests to the deepseek-v4.1-flash model on Ollama were charged at an incorrect rate, leading to higher usage consumption than expected for certain users. Sorry about th

model-releasesollama--x

Overlay_dx - Automating forecasting evaluation

arXiv:2609.24586v1 Announce Type: new Abstract: Traditional evaluation metrics provides numerical values but often lack comprehensibility, hindering effective differentiation of model performances. Ou

P2Flow: Phoneme-aware Progressive Flow Matching for Extreme Speech Super-Resolution

arXiv:2609.24138v1 Announce Type: cross Abstract: Generative models have recently demonstrated considerable promise in speech super-resolution (SSR). Nevertheless, the majority of existing work has co

Tutorials

PAC-Bayesian Meta-Learning for Few-Shot Identification of Linear Dynamical Systems

arXiv:2609.24117v1 Announce Type: new Abstract: Identifying linear time-invariant (LTI) dynamical systems is challenging when trajectories are short, noisy, or high-dimensional. Traditional system ide

tutorialsarxiv-cs-lg

PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Models

arXiv:2609.23574v1 Announce Type: cross Abstract: In high-dimensional tabular learning, feature screening provides a lightweight, model-agnostic way to remove irrelevant features before model fitting.

PackLab: A Comprehensive Framework for Developing, Training, and Evaluating MLLMs in Robotic Bin Packing

model-releasesarxiv-cs-ro

arXiv:2609.23784v1 Announce Type: new Abstract: Robotic bin packing requires long-horizon sequential decision-making, as each object placement affects the available space for subsequent packing. Exist

PADiff: Predictive and Adaptive Diffusion Policies for Ad Hoc Teamwork

arXiv:2511.07260v3 Announce Type: replace-cross Abstract: Ad hoc teamwork (AHT) requires agents to collaborate with previously unseen teammates, which is crucial for many real-world applications. The

PAGE: Partition-Aware Gated KV-Cache Eviction

arXiv:2609.22157v1 Announce Type: cross Abstract: KV-cache eviction methods decide which tokens to keep but not whether to evict at all, so a benchmark mean can hide a class of inputs on which compres

PanoSeg3R: Feed-Forward 3D Semantic Segmentation for Panoramic Images with an Automatic Data Curation Pipeline

arXiv:2609.22687v1 Announce Type: new Abstract: We present PanoSeg3R, a feed-forward framework for 3D panoramic semantic segmentation. Unlike existing methods designed for perspective inputs, PanoSeg3