Search: “governance”

When Should AI Follow? Task Structure and Joint Adaptation by Human and AI Agents

arXiv:2504.20903v4 Announce Type: replace-cross Abstract: How should organizations divide and sequence decision tasks between human and artificial agents? We develop a computational model of joint seq

local-aiarxiv-cs-ai

31 Jul 2026

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A Compositional Theory of Causally Masked Transformers

DGX agent

arXiv:2607.26988v1 Announce Type: cross Abstract: What types of decision problems can a causally masked, finite-precision transformer solve for inputs of arbitrary length? Existing answers often rely

researcharxiv-cs-lg

30 Jul 2026

AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-Playing

model-releasesarxiv-cs-cl

arXiv:2601.11007v2 Announce Type: replace-cross Abstract: LLM role-playing aims to portray arbitrary characters in interactive narratives, yet existing systems often suffer from limited immersion and

AIGen: Automating AI Bill of Materials Generation Through Hybrid MLOps Integration

arXiv:2607.26652v1 Announce Type: new Abstract: The responsible development and deployment of artificial intelligence (AI) systems requires rigorous documentation of their constituent artifacts, e.g.,

Between Gradient and Natural Gradient: A Continuum of LoRA Initializations

arXiv:2607.26247v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) fine-tunes large pretrained models at a fraction of the cost of full fine-tuning, but its performance depends strongly on how

ContactFlow: A video action conditioning that transfers across embodiments

arXiv:2607.26579v1 Announce Type: cross Abstract: World models offer a promising route toward robot planning by enabling agents to imagine and verify the consequences of actions before execution. Howe

applicationsarxiv-cs-cv

Denoising growth complexity: Data geometry and certified schedules for diffusion sampling

arXiv:2607.26285v1 Announce Type: cross Abstract: Two central challenges in diffusion-based sampling are the theoretical one of understanding their remarkable effectiveness even in high-dimensional se

EgoSafe: A First-Person Mobile-Captured Benchmark for Visual Safety Understanding

model-releasesarxiv-cs-cv

arXiv:2607.26518v1 Announce Type: new Abstract: Reliable visual safety understanding in real-world scenarios demands more than just object recognition; it requires causal reasoning under epistemic unc

Exclusive: Upwind adds context scanning for AI agents as AI DR hits general availability

Cloud security startup Upwind Security Inc. today unveiled AI Agent Context Scanner, which inspects the instructions, tools and connections feeding artificial intelligence agents before those agents a

agentssiliconangle

FakeIDet3-DB: Refining Digital Attacks and Patch Extraction for Secure ID Benchmarking

arXiv:2607.26641v1 Announce Type: new Abstract: Identity document (ID) authentication relies on the structural integrity of complex, high-frequency security patterns. However, advanced Generative AI m

local-aiarxiv-cs-cv

From Classification to Regression: Using a Fruitfly to Solve Equations

arXiv:2607.27196v1 Announce Type: new Abstract: We present a novel approach to regression tasks using classification which is motivated by the mechanism used by fruitflies to sense their environment.

local-aiarxiv-cs-lg

Journey Operators for Structured Multi-Axis Composition

arXiv:2607.26775v1 Announce Type: new Abstract: Many kinds of data have structure along one or more axes: words in a sentence, pixels in an image, nodes in a tree, frames in audio, or cells in a 3D vo

safetyarxiv-cs-lg

Local-first personal AI agent that runs on Ollama + Telegram — looking for feature ideas

I’ve been building ClawLite, an open-source personal AI assistant that talks to you through Telegram and defaults to Ollama (local models). What it does: Multi-agent research with actual cross-source

local-air-ollama

OpenAI says it is cutting the price of GPT-5.6 Luna by ~80% and the price of GPT-5.6 Terra by 20% after improving the efficiency of the systems that serve them (Ina Fried/Axios)

Ina Fried / Axios: OpenAI says it is cutting the price of GPT-5.6 Luna by ~80% and the price of GPT-5.6 Terra by 20% after improving the efficiency of the systems that serve them — OpenAI said Thursda

model-releasestechmeme

Rethinking Self-Evolution: A Constrained Exploration-Exploitation Process for Mitigating Skill Overfitting

arXiv:2607.26643v1 Announce Type: cross Abstract: Enabling large language model (LLM) agents to accumulate and reuse experience from past interactions remains a central challenge in real-world applica

Semi-Decentralized Multi-Spacecraft Collision Avoidance under Communication Constraints

arXiv:2607.26570v1 Announce Type: new Abstract: Current spacecraft collision-avoidance operations rely on intermittent ground-station contacts, requiring operators to plan with delayed and asynchronou

agentsarxiv-cs-ro

Stable and Budget-Feasible Coalition Formation for Clustered Federated Learning: A Hedonic Potential-Game Approach

arXiv:2607.26788v1 Announce Type: cross Abstract: Clustered federated learning benefits from organizing heterogeneous participants into coalitions that train coalition-specific models, but such cluste

safetyarxiv-cs-lg

Tutorials

StatePlay: State-Aware Game World Models for Mechanics-Consistent Generation

arXiv:2607.26754v1 Announce Type: new Abstract: Recent game world models can generate visually realistic and interactive environments conditioned on player actions. However, games are not defined by p

tutorialsarxiv-cs-cv

Towards Trustworthy Embodied Intelligence: A Systems Framework and Graded Trustworthiness Levels

model-releasesarxiv-cs-ro

arXiv:2607.26121v1 Announce Type: new Abstract: Embodied intelligence integrates learned perception and decision making with real-time computation, control, and physical interaction. Because failures

Automate data monitoring and root-cause analysis with Looker Agentic Workflows

model-releasesgoogle-cloud-ai

Traditional business intelligence alerts can only tell you that a metric changed, leaving data analysts to manually hunt through dashboards to figure out why. Today, we are introducing Looker Agentic

Conformal Cascade: Distribution-Free Accuracy Guarantees for Multi-Tier LLM Inference

arXiv:2607.25018v1 Announce Type: new Abstract: Large language model (LLM) cascades reduce inference cost by routing easy queries to a small model and deferring hard queries to a larger one. Productio

DDSNet: Dual-domain Symmetry-aware Network for PCSEL Property Prediction

arXiv:2607.24785v1 Announce Type: cross Abstract: Efficient exploration of the photonic crystal (PhC) lattice design space is essential for developing photonic crystal surface-emitting lasers. While c

Dual-Level Atomic and Coordination Geometry Learning for Crystal Property Prediction Using Graph Neural Networks

model-releasesarxiv-cs-ai

arXiv:2607.24818v1 Announce Type: cross Abstract: Accurate prediction of crystal properties remains a key challenge in computational materials science. While graph neural networks (GNNs) such as CGCNN

Explanation-Bound Tool Execution for AI Agents: Server-Verified Action Claims Without Trusting Model Rationales

arXiv:2607.25364v1 Announce Type: new Abstract: Tool-using agents expose structured calls but commonly attach free-form rationales. Such rationales are neither authorization nor reliable introspection

Foundation Models for EEG Are Blind to Long-Range Temporal Correlations: A Spectral-Temporal Dissociation Behind Their Cross-Population Fragility

arXiv:2607.24834v1 Announce Type: cross Abstract: Objective. Electroencephalography (EEG) foundation models (FMs) are trained to reconstruct or contrastively align short patches, then pooled into a fi

researcharxiv-cs-ai

Learned, Relied Upon, or Necessary? Separating Checkpoint Dependence from Task-Level Value in Sheaf GNNs

arXiv:2607.25387v1 Announce Type: new Abstract: Learned restriction maps in sheaf graph neural networks are often treated as proof that the model has discovered useful edge geometry. That conclusion d

On benchmarking long-context agentic instruction following. Agent benchmarks mostly reward reaching the answer. This new benchmark measures …

On benchmarking long-context agentic instruction following. Agent benchmarks mostly reward reaching the answer. This new benchmark measures whether the agent reached it the permitted way, which is the

model-releasesdair-ai--x

Physics-Aware End-to-End Deep Reinforcement Learning for Quadcopter Control with Actuator Dynamics

arXiv:2607.25985v1 Announce Type: cross Abstract: Unmanned aerial vehicles (UAVs), particularly quadcopters, present unique challenges for autonomous control due to their underactuated dynamics: only

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests

arXiv:2509.19710v2 Announce Type: cross Abstract: Symbolic regression has emerged as a powerful tool for artificial intelligence-driven scientific discovery by learning interpretable analytical expres

Quotient Dynamics, Effective Curvature, and Implicit Bias in Positive Quadratic Networks

arXiv:2607.25624v1 Announce Type: new Abstract: Positive quadratic networks admit the low-rank representation f_U(x)=x^top UU^top x, where Uinmathbb{R}^{dtimes r} is identifiable only up to right orth

SpectONet: A Physics-Guided Spectral Deep Operator Network for Euler-Bernoulli Beam Dynamics

arXiv:2607.25790v1 Announce Type: cross Abstract: This paper proposes a novel physics-guided spectral deep operator network, termed SpectONet, for solving Euler-Bernoulli beam (EBB) vibration problems

applicationsarxiv-cs-ai

The Disruptive Impact of Large Language Models on Capture the Flag Competitions and the Path Toward Fair Play

arXiv:2607.25425v1 Announce Type: new Abstract: Capture the Flag (CTF) competitions are among cybersecurity's most effective training grounds, developing practical skill across cryptography, web explo

The openai agent sandbox escape actually has very real implications for the diffusion of AI in the enterprise. The incident showed the power…

The openai agent sandbox escape actually has very real implications for the diffusion of AI in the enterprise. The incident showed the power and capability of agents, and the need to harden systems an

agentsgary-marcus--x

Industry

The Time Traveler’s Satchel - Fictional photographs from Human History, created with ChatGPT Sol5.6 Max Work Mode (Part 1)

Quick clarification before opening the bag: every image here is fictional and AI-generated. These are not real archival discoveries or claims about hidden history. This series grew out of two earlier

industryr-chatgpt

The User Asks, Platforms Compete: How Agentic Recommendation Markets Take Shape

arXiv:2607.25253v1 Announce Type: new Abstract: Online recommendation has traditionally taken place after a user enters a platform, which determines the candidate pool and the ranking shown to the use

agentsarxiv-cs-ai

Towards real-time surrogate-free Bayesian inversion for neutron reflectometry

arXiv:2509.06924v3 Announce Type: replace Abstract: Neutron reflectometry (NR) is a key enabling technology for many areas of scientific development. Although the forward reflectivity model is well-kn

Tutorials

Unifying Active Learning and Semi-Supervised Learning for Medical Image Segmentation

arXiv:2607.25014v1 Announce Type: new Abstract: In practical settings, medical image segmentation models are often developed with limited annotated data rather than fully labeled datasets. Training fr

tutorialsarxiv-cs-cv

When Algorithms Meet Artists: Semantic Compression and Stake-holder Marginalisation in Public AI-Art Discourse (2013-2025)

arXiv:2508.03037v5 Announce Type: replace Abstract: Artists occupy a paradoxical position in generative AI. Their own work trains models that now compete with them, replicate their styles, and reshape

applicationsarxiv-cs-cl

When Does Legacy Data Start to Help? Emergent Transfer in Cross-Configuration Robot Learning

arXiv:2607.25593v1 Announce Type: new Abstract: Robotic hardware evolves over time, but demonstration data is often tied to a specific sensor and actuator configuration. This raises a practical and un

safetyarxiv-cs-ro

WHTMix: Efficient Stereo Depth Estimation via Walsh-Hadamard Token Mixing

arXiv:2607.25234v1 Announce Type: new Abstract: Stereo depth estimation for driving, robotics and augmented reality must run at high resolution under tight latency budgets, yet in transformer-based ma

researcharxiv-cs-cv

A Mechanistic Perspective and Circuit-Guided Difficulty Metric for Unlearning

arXiv:2601.09624v2 Announce Type: replace-cross Abstract: Machine unlearning is becoming essential for building trustworthy and compliant language models. Yet unlearning success varies considerably ac

researcharxiv-cs-ai

Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents

model-releasesarxiv-cs-ai

arXiv:2607.24625v1 Announce Type: cross Abstract: Autonomous LLM agents processing mixed-confidentiality data face severe security risks from prompt injection attacks and reasoning errors. While dynam

Agentic Reward Modeling: Verifying GUI Agent via Progressive Trajectory-Grounded Interaction

arXiv:2602.00575v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a promising pathway for continuously advancing GUI agents, yet existing reward modeli

agentsarxiv-cs-ro

Artificial Intelligence and Innovation Ecosystem: Evolutionary Developments, Challenges, and Future Directions

arXiv:2607.24589v1 Announce Type: new Abstract: The development of the Innovative Ecosystem (IE) presents a new paradigm for economic integration, collaborative advancement, and shared achievements. T

applicationsarxiv-cs-ai

Discrepancy-Rounded Fair Bandits with Static and Time-Varying Exposure Floors

arXiv:2607.22935v1 Announce Type: new Abstract: Minimum-exposure constraints arise in recommendation, content curation, and regulated allocation when each provider, arm, or group must receive guarante

Efficiency Matters in Autonomous Research

arXiv:2607.24647v1 Announce Type: new Abstract: AI-driven autonomous research (AR) systems are becoming increasingly effective across a broad range of tasks. Their performance, however, is still evalu

FeelWorld: Visuo-Tactile World Model for Hierarchical Contact Prediction and Planning

arXiv:2607.24267v1 Announce Type: new Abstract: Humans plan physical interactions by imagining the possible outcomes of candidate actions. However, existing visual world models primarily capture appea

researcharxiv-cs-ro

From Cognitive Architectures to Language Agents: A Mechanism-Level Review of Lineage, Convergence, and Migration Gaps

arXiv:2607.23942v1 Announce Type: new Abstract: Memory, planning, reflection, and tool use are often compared as feature labels, obscuring the control semantics that determine how an agent actually ru

agentsarxiv-cs-ai