All entries

Obshazard-bench: Benchmarking Multimodal Foundation Models for Real-Time Disaster Intelligence from Raw Earth Observation Streams

arXiv:2608.00012v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly used to interpret Earth observation data, yet their capability to support real-world disaster

Agents

Obsidian Security raises $85M as AI agents create cybersecurity’s next major attack surface

DGX agent

Obsidian Security Inc. has raised an 85 million Series D funding round at a post-money valuation of 1.1 billion as enterprises increasingly look to secure autonomous artificial intelligence agents acc

agentssiliconangle

4 Aug 2026

Applications

OC-VLA++: Monocular Geometry-Guided Cross-View Consistency for Viewpoint-Robust Robotic Manipulation

arXiv:2608.01066v1 Announce Type: new Abstract: We propose OC-VLA++, an extension of OC-VLA for viewpoint generalization under limited camera coverage. While OC-VLA grounds robot actions in the camera

applicationsarxiv-cs-ro

OmniAI: A Surface-Adaptive Aerial Projection Interface for Human--Drone Interaction

arXiv:2608.00721v1 Announce Type: new Abstract: Drones in human environments often lack spatially grounded in- terfaces for situated communication. We present OmniAI, an em- bodied aerial agent that s

agentsarxiv-cs-ro

On the Identifiability of Masked Prediction: Mode Blindness and Mask Schedules

arXiv:2608.01383v1 Announce Type: new Abstract: Masked prediction learns representations by fitting a schedule-weighted family of conditional laws, but it remains unclear when near-optimal conditional

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies

arXiv:2608.01041v1 Announce Type: cross Abstract: Machine-learning predictors estimate processor performance far faster than cycle-level simulation. For design-space exploration, however, the valuable

On the Limits of Support-Preserving Alignment and Bounded Filtering

arXiv:2607.18295v2 Announce Type: replace Abstract: We study whether alignment schemes that reshape a base model's output distribution, combined with bounded safety filters, can drive the probability

safetyarxiv-cs-lg

On the Viability of Semi-Supervised Segmentation Methods for Statistical Shape Modeling

arXiv:2407.15260v3 Announce Type: replace Abstract: Statistical Shape Models (SSMs) excel at identifying population level anatomical variations, which is at the core of various clinical and biomedical

On the Wings of Imagination: Conflicting Script-based Multi-role Framework for Humor Caption Generation

arXiv:2602.06423v2 Announce Type: replace Abstract: Humor is a commonly used and intricate human language in daily life. Humor generation, especially in multi-modal scenarios, is a challenging task fo

researcharxiv-cs-cl

Onboard Satellite Image Classification for Earth Observation: A Comparative Study of ViT Models

arXiv:2409.03901v4 Announce Type: replace Abstract: Remote sensing (RS) image classification is central to Earth observation, but onboard deployment requires models that are accurate, efficient, and r

researcharxiv-cs-cv

One QK Channel, Many Sources: Guarding Low-Precision Attention Collapse

model-releasesarxiv-cs-lg

arXiv:2608.02091v1 Announce Type: new Abstract: A bfloat16 transformer can train normally for many steps and then collapse abruptly. Distinct low-precision errors can trigger the same failure, leaving

One Query, Many Scales: Sparse Mixture-of-Experts for Efficient Hierarchical Cross-View Geo-Localization

arXiv:2608.01060v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL) retrieves geo-tagged satellite imagery for a ground-view query. Most systems exhaustively search a flat, fixed-resolu

One-Sided Quantile Coupling for Flow Matching

arXiv:2608.00978v1 Announce Type: cross Abstract: Flow Matching trains continuous-time generative models by regressing the velocity field of a probability path between a simple source distribution and

safetyarxiv-cs-cv

one thing i appreciate about silico is that it's a deeply humanist product. we designed silico to keep you in the experimental loop -- more …

model-releaseslinus-lee--x

one thing i appreciate about silico is that it's a deeply humanist product. we designed silico to keep you in the experimental loop -- more observable, easier to steer, easier to understand we want to

onepot-Bench 0: towards lab-aware in silico chemistry benchmarks

model-releasesarxiv-cs-lg

arXiv:2608.02595v1 Announce Type: new Abstract: Language models are playing an increasingly important role in laboratory science, performing tasks such as experiment planning, execution, and post-hoc

Online Algorithms via Minimax and Posterior Matching

arXiv:2608.01616v1 Announce Type: new Abstract: Competitive analysis is central to the study of online algorithms, but upper bounds are often highly problem-specific. We develop a more unifying method

OoO-Spec: Out-of-Order Semantic Speculation for Fast Tool Calling

arXiv:2608.00814v1 Announce Type: new Abstract: LLMs generate tool calls token by token, even though the function choice and argument values can often be predicted in parallel from the request and too

Open-DiffLoco: Open-Source Differentiable Learning for Deployable Blind Quadruped Locomotion

arXiv:2608.02069v1 Announce Type: cross Abstract: Developing deployable locomotion policies through conventional reinforcement learning often requires complex reward engineering and expensive training

local-aiarxiv-cs-lg

Hardware

Open Secure AI Alliance proposes SAFE guidelines as membership tops 120

The Open Secure AI Alliance today proposed a set of guidelines for reporting cybersecurity incidents involving artificial intelligence agents, one week after the group was formed. The proposal is call

hardwaresiliconangle

Open-Set Visual Text Forensics via Sparse-Constraint Rectified Flow

arXiv:2608.02258v1 Announce Type: new Abstract: Rapidly evolving Generative AI enables sophisticated visual text manipulations that increasingly evade current forensic detectors. Existing discriminati

local-aiarxiv-cs-cv

OpenAI and Anthropic have both just posted about an overlapping cyber incident involving GPT-5.6-Sol and Mythos 5 during an evaluation by UK…

model-releasesgary-marcus--x

OpenAI and Anthropic have both just posted about an overlapping cyber incident involving GPT-5.6-Sol and Mythos 5 during an evaluation by UKAISI. I will quote: 'In the most serious case, an agent trie

Applications

OpenAI drags Apple’s lawsuit into the court of public opinion

Apple's legal battle against OpenAI just got messier now that the ChatGPT-maker has publicly aired receipts to counter Apple's version of events. In a blog post published overnight titled 'Apple is ge

applicationsthe-verge-ai

Industry

OpenAI publicly pushes back against Apple lawsuit after new filing

OpenAI Group PBC has publicly pushed back against a lawsuit that Apple Inc. filed against it last month. The ChatGPT developer outlined its arguments in a blog post published on Monday. The move came

industrysiliconangle

OpenAI says one of its models exploited a website after third-party AI security lab Irregular mistakenly gave it access to the internet during evaluations (Wired)

Wired: OpenAI says one of its models exploited a website after third-party AI security lab Irregular mistakenly gave it access to the internet during evaluations — Rogue AI agents from OpenAI and Anth

agentstechmeme

OpenART: Scaling Agent Red Teaming via Open-Ended Environment Evolution

arXiv:2608.00677v1 Announce Type: new Abstract: AI agents operate in persistent environments where early state changes can influence decisions far into the future. Unlike conventional language-model i

OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset

arXiv:2406.14657v4 Announce Type: replace Abstract: We introduce OpenDebateEvidence, a comprehensive dataset for argument mining and summarization sourced from the American Competitive Debate communit

researcharxiv-cs-cl

Opt.Gear Technical Report

arXiv:2608.01034v1 Announce Type: new Abstract: We introduce Opt.Gear, a foundation model designed for efficient on-device deployment, real-tim inference, and strong task capability. It includes a den

Applications

Optical Flow from Photons

arXiv:2608.00499v1 Announce Type: new Abstract: Optical flow remains challenging in high-speed and low-light scenes, where the limited frame rate and sensitivity of conventional cameras lead to motion

applicationsarxiv-cs-cv

Optimal Unambiguous DNFs and Alon-Saks-Seymour

arXiv:2608.02533v1 Announce Type: cross Abstract: We construct unambiguous DNFs having width O(n) but 0-certificate complexity Omega(n^2). By utilizing the special structure of these DNFs, we prove a

Tutorials

Optimized Piecewise Affine Abstractions of Neural Networks with Learnable Activation Functions

arXiv:2602.06737v2 Announce Type: replace Abstract: We present a generalized framework for the range verification of neural networks featuring non-linear activation functions. Our approach first const

tutorialsarxiv-cs-lg

Optimizing Minimax Regret in Uncertain MDPs with Small Sets of Policies

arXiv:2608.02509v1 Announce Type: cross Abstract: Sequential decision-making in real-world applications often involves uncertainty about the environment's model. Uncertain Markov decision processes (U

safetyarxiv-cs-lg

ORCA: ORgan-Centroid Aggregation for Training-Free 3D CT Visual Token Compression

arXiv:2608.00345v1 Announce Type: new Abstract: A 3D CT scan entering a vision-language model produces a long sequence of visual tokens, often thousands to tens of thousands per volume, and this seque

ORCESTRA: VLM-driven Visual Robot programming in Mixed Reality

arXiv:2608.00775v1 Announce Type: cross Abstract: ORCESTRA is a mixed-reality system for programming robot digital twins through no-code waypoint teaching and language-guided control. In a passthrough

safetyarxiv-cs-cv

Orchestrating Dual-Boundaries: An Arithmetic Intensity Inspired Acceleration Framework for Diffusion Language Models

arXiv:2511.21759v2 Announce Type: replace Abstract: Diffusion-based large language models (dLLMs) have recently gained significant attention for their exceptional performance and inherent potential fo

researcharxiv-cs-cl

OSMDA: OpenStreetMap-based Domain Adaptation for Remote Sensing VLMs

arXiv:2603.11804v3 Announce Type: replace Abstract: Vision-Language Models (VLMs) adapted to remote sensing rely heavily on domain-specific image-text supervision, yet high-quality annotations for sat

safetyarxiv-cs-cv

OSSDD - a New Open Dataset for Sentinel-1 Ship Detection

arXiv:2608.01963v1 Announce Type: new Abstract: Ship detection in Synthetic Aperture Radar (SAR) images plays an important role for maritime situational awareness, especially with respect to different

researcharxiv-cs-cv

OTAP: Structure-Aware Optimal Transport for Evaluating Planning and Execution in Agent Trajectories

arXiv:2607.17082v2 Announce Type: replace-cross Abstract: Large language model agents solve tasks by generating trajectories that interleave planning, tool calls, and intermediate results. Current eva

agentsarxiv-cs-cl

PackingGPT: 3D Packing Agent for Real Furniture in Last-Mile Delivery

arXiv:2608.01427v1 Announce Type: new Abstract: 3D bin packing rectangular items into standardised containers to maximise space utilisation under geometric shipping automation. Loading a furniture pur

PALMs: Using Multi Construct-Grounded Rationales for Modeling Population Preferences in LLMs

arXiv:2608.01458v1 Announce Type: new Abstract: Large language models are being extensively used to simulate individual user behavior, yet faithfully representing a population requires capturing the s

safetyarxiv-cs-cl

Parameter-Dynamic Adaptive Fusion and Calibration Network for RGBT Tracking

arXiv:2608.01807v1 Announce Type: new Abstract: Existing RGBT trackers typically employ fusion functions with fixed parameters across different targets and scenarios. Although dynamic-architecture met

Parameter-Efficient CLIP Adaptation for 3D Understanding via Unified Tokenization

arXiv:2505.18819v2 Announce Type: replace Abstract: Vision-language models, such as CLIP, encode rich semantic knowledge through large-scale image-text pretraining. Reusing these models for 3D underst

Paris as a 15-Minute City: An Explainable AI Perspective

arXiv:2608.00815v1 Announce Type: new Abstract: The 15-minute city promotes access to everyday services within a short walk or bicycle ride, but its relationship with observed mobility remains difficu

local-aiarxiv-cs-lg

Parsing a W-2 into markdown was always the easy part. Getting the fields out was a second pipeline: define a schema, map the fields, handle …

Parsing a W-2 into markdown was always the easy part. Getting the fields out was a second pipeline: define a schema, map the fields, handle the edge cases. Set processing_options.forms='𝗲𝗻𝗿𝗶𝗰𝗵', and L

agentsjerry-liu--x

Hardware

Partial FC: Training 10 Million Identities on a Single Machine

arXiv:2010.05222v3 Announce Type: replace Abstract: Training face recognition models with millions of identities is challenging because classifier storage, logit memory, and computation grow linearly

hardwarearxiv-cs-cv

Partially-Observable Transmission Control for UAV-Enabled Federated Learning in IoT Networks

arXiv:2608.00855v1 Announce Type: cross Abstract: Uncrewed aerial vehicle (UAV)-enabled federated learning (FL) can provide flexible, on-demand edge intelligence for large-scale IoT deployments, but o

safetyarxiv-cs-lg

Tutorials

PartMat: Material-Aware 3D Part Decomposition with a Single Global Latent

arXiv:2608.01825v1 Announce Type: new Abstract: Part-level 3D generation has recently attracted increasing attention for producing structured and editable 3D assets. However, existing methods typicall

tutorialsarxiv-cs-cv

Passing Coarse Marginal Checks Can Be Cheap: Persona Mixtures and Imprecise Treatment-Response Estimates in an LLM Persona Panel

arXiv:2608.00979v1 Announce Type: cross Abstract: Large language models are increasingly used as synthetic research participants and are often validated by whether their marginal responses resemble hu

PatchAlign3D: Local Feature Alignment for Dense 3D Shape Understanding

arXiv:2601.02457v2 Announce Type: replace Abstract: Current foundation models for 3D shapes excel at global tasks (retrieval, classification) but transfer poorly to local part-level reasoning. Recent

local-aiarxiv-cs-cv