Search: “persistence”

Nanoparticle Networks for Neuromorphic Computing

arXiv:2607.27844v1 Announce Type: cross Abstract: Physical computing leverages complex dynamical systems for energy-efficient data processing. In this work, we present a neuromorphic architecture base

OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval

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DGX agent

arXiv:2607.27475v1 Announce Type: cross Abstract: In modern recommendation systems, retrieval serves as a primary stage responsible for filtering billions of candidate items down to thousands prior to

safetyarxiv-cs-lg

31 Jul 2026

RedFlow: Redirect Failure into Action-Level Corrections for Flow-matching VLA Policy

model-releasesarxiv-cs-ro

arXiv:2607.27782v1 Announce Type: new Abstract: Flow-matching Vision-Language-Action (VLA) policies have shown strong potential for robotic manipulation but often suffer from compounding errors caused

StealthBench: Measuring Operational Stealth in Autonomous Offensive-Security Agents

model-releasesarxiv-cs-ai

arXiv:2607.26314v1 Announce Type: cross Abstract: Stealth, the discipline of achieving an objective without revealing your presence, capabilities, or collected intelligence, is what separates sophisti

The Convergence Behavior of Adam under Heavy-Tailed Noise

arXiv:2607.27383v1 Announce Type: new Abstract: We establish the first convergence guarantees for the plain vector-form Adam optimizer under heavy-tailed stochastic noise. While several Adam variants

TopoFormer: Topology Meets Attention for Graph Learning

arXiv:2607.28259v1 Announce Type: new Abstract: We introduce Topoformer, a lightweight and scalable framework for graph representation learning that encodes topological structure into attention-friend

Towards Generalized Synapse Detection Across Invertebrate Species

model-releasesarxiv-cs-cv

arXiv:2509.17041v2 Announce Type: replace Abstract: Behavioural differences across organisms, whether healthy or pathological, are closely tied to the structure of their neural circuits. Yet, the fine

Local Ai

Write-Safe Flow Field Mapping under Ambiguous Onboard Sensing and Localization Drift

arXiv:2607.27713v1 Announce Type: new Abstract: Mobile robots can infer local flow structure from onboard sensing, but a locally plausible estimate is not always safe to write into a global map. Simil

local-aiarxiv-cs-ro

Collaborative Weighting with Pessimistic Critic for Mitigating Overestimation in Off-Policy Reinforcement Learning

arXiv:2607.26509v1 Announce Type: new Abstract: Deep off-policy reinforcement learning algorithms for continuous control typically rely on neural value function approximation to guide policy improveme

safetyarxiv-cs-lg

Constitutional Midtraining: Content Presence Drives Alignment Gains

arXiv:2607.26654v1 Announce Type: new Abstract: Post-training alignment is often shallow, eroding under fine-tuning. Whether midtraining interventions, cleanly isolated from post-training, can produce

safetyarxiv-cs-cl

Deep Expert Injection for Anchoring Retinal VLMs with Domain-Specific Knowledge

arXiv:2603.07131v4 Announce Type: replace Abstract: Large Vision Language Models (LVLMs) show immense potential for automated ophthalmic diagnosis. However, their clinical deployment is severely hinde

researcharxiv-cs-cv

Do more with less: How GKE can reduce your cost per agent by 75%

In today’s agentic era, modern cloud applications are evolving from a set of passive tools to fleets of autonomous digital workers that reason, plan, and take action across a wide range of tasks. For

agentsgoogle-cloud-ai

Do You Really Need to Pretrain Q-Functions for Online RL Fine-Tuning?

arXiv:2607.27203v1 Announce Type: new Abstract: Pre-training followed by fine-tuning has become the dominant recipe for learning performant policies, and in value-based reinforcement learning (RL) thi

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Equilibrium Training of Energy-Based Models with Parallel Trajectory Tempering

arXiv:2607.27077v1 Announce Type: new Abstract: Energy-Based Models (EBMs) provide an interpretable framework for generative modeling of scientific data, but poor Markov Chain Monte Carlo mixing often

EvoPINN: Agentic Discovery of Executable Algorithms for Physics-Informed Neural Networks

arXiv:2607.26490v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful paradigm for solving partial differential equations (PDEs), yet their performance

Tutorials

Explicit Kinematic Guidance from Analytic Concepts for Vision-Language-Action Models

arXiv:2607.26513v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models rely mainly on 2D inputs, neglecting the rich object structural information and commonsense knowledge inhere

tutorialsarxiv-cs-ro

Hardware

Four Ways to Deploy More Secure AI Agents

NVIDIA’s AI Red Team found common failure modes in enterprise AI agents: weak access controls, unrestricted code execution via tools, unprotected network egress, and exposure of plaintext secrets. The

hardwarenvidia-developer

Lilith: Backdoor Generalization under Training-Inference Trigger Shift

arXiv:2607.26099v1 Announce Type: cross Abstract: Machine-learning services increasingly rely on public data, third-party providers, and outsourced training, creating opportunities for data-poisoning

safetyarxiv-cs-lg

Living-Harness Is an Interactive-Agent Evolver

arXiv:2607.26598v1 Announce Type: cross Abstract: Large language model (LLM) agents may recover from a failure within an episode or after a retry, yet the same execution failure can recur in later tas

agentsarxiv-cs-cl

Metis: Memory Foundation Model

arXiv:2607.26760v1 Announce Type: new Abstract: Recent advances in AI agents have increasingly internalized native capabilities into their underlying foundation models, giving rise to multimodal found

agentsarxiv-cs-cl

On the robustness of noisy solutions in non-convex neural networks

arXiv:2607.27000v1 Announce Type: cross Abstract: Optimization in non-convex neural network models is strongly influenced by the geometry of the solution space: sparse, isolated, point-like clusters a

one of the top cybersecurity models, post-trained from open weights by @depthfirstlabs on @FireworksAI_HQ long-horizon RL is as much an infr…

one of the top cybersecurity models, post-trained from open weights by @depthfirstlabs on @FireworksAI_HQ long-horizon RL is as much an infra problem as a research one: 100+ turn rollouts, async/pipel

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P.A.I. — Sleek Native Desktop AI Overlayer for Local Ollama Models 🤖⚡

Greetings Community! 👋 I hope everyone is doing well! I'm Tauhid — Senior EEE student from a Bangladeshi University Today I'd like to share an open-source project I’ve been developing called P.A.I. (P

model-releasesr-ollama

Searching for Robust Augmentations to Improve Out-of-Domain Generalization in Dermoscopic Skin Cancer Classification

arXiv:2607.26765v1 Announce Type: new Abstract: Background/Objectives: Dermoscopic skin lesion classifiers often lose accuracy under domain shift across imaging devices, illumination, and capture arti

safetyarxiv-cs-cv

Simultaneous Coverage and Efficiency Guarantee in Online Conformal Prediction

arXiv:2607.26577v1 Announce Type: new Abstract: Adaptive conformal inference (ACI) of Gibbs and Cand{es and its variants are the standard approach to online conformal prediction under distribution shi

Skillful forecasting of offshore winds from satellite scatterometer constellations

arXiv:2607.27152v1 Announce Type: new Abstract: Accurate intraday forecasts of offshore wind are becoming increasingly important for power system operation and the integration of growing shares of off

Structurally Separated Uncertainty in Supervised Latent Variable Models

arXiv:2602.11219v2 Announce Type: replace Abstract: Predictive uncertainty is commonly decomposed into epistemic and aleatoric components, but standard decompositions often produce strongly correlated

What Can Latent World Models Know? Physical Parameter Identifiability in Multimodal Predictive Representations

arXiv:2607.27017v1 Announce Type: new Abstract: A central premise of latent world models is that predicting the future forces a representation to internalize the physics of its environment. Which phys

WikiLoop: Jointly Learning to Build and Navigate Agent-Native Wikis with Downstream Feedback

arXiv:2607.26604v1 Announce Type: new Abstract: Knowledge-base construction and querying are typically optimized in isolation: retrieval-augmented agents operate over a fixed, externally maintained in

safetyarxiv-cs-cl

A Study of Crosslinguistic Influence in Language Models

arXiv:2601.21587v2 Announce Type: replace Abstract: The sequential acquisition of languages inevitably leads to Crosslinguistic Influence (CLI), where the syntactic properties of a first language (L1)

researcharxiv-cs-cl

Applications

A2TTA: Anchored-and-Agile Test-Time Adaptation for Evolving Traffic Sensor Networks

arXiv:2607.25875v1 Announce Type: cross Abstract: Traffic forecasting is important for efficient traffic management and route planning in smart cities. Existing traffic forecasting studies typically a

applicationsarxiv-cs-ai

Agentic AI for Scientific Reasoning in Autonomous Quantum Sensing Experiments

model-releasesarxiv-cs-ai

arXiv:2607.25145v1 Announce Type: cross Abstract: We implement an agentic AI workflow built around a large language model (LLM) agent for autonomous experiments with nitrogen-vacancy (NV) centers in d

Tutorials

Analysis of the Shortcut Learning and Clever Hans Effect in CNN based ECG Image Classification

arXiv:2607.25117v1 Announce Type: cross Abstract: Deep learning models for ECG image classification may achieve high accuracy by exploiting non-physiological visual cues instead of ECG waveform morpho

tutorialsarxiv-cs-ai

Automate your agent development lifecycle using any coding agent

model-releasesgoogle-cloud-ai

Welcome to our latest Gemini Enterprise Agent Platform deep dive, a practical walkthrough where we’ll teach you how to build real-world, production-ready agents starting from step 1. If you haven’t al

Beyond Facial Consistency: Personalized Person Image Generation with Holistic Identity Preservation

model-releasesarxiv-cs-cv

arXiv:2607.25622v1 Announce Type: new Abstract: Personalized person image generation requires preserving subject identity across both local facial details and broader appearance cues. Existing methods

Beyond Memory: A Templated Substrate for Heterogeneous Collaborative Knowledge Work with LLM Agents

arXiv:2607.24759v1 Announce Type: new Abstract: Research projects, educational efforts, and adjacent knowledge work accumulate findings, decisions, and reasoning that future collaborators rarely recov

agentsarxiv-cs-ai

Breaking the Curse of Repulsion: Remoteness-Aware Control of Negative Off-Policy Updates

arXiv:2602.10430v2 Announce Type: replace-cross Abstract: Off-policy policy optimization reuses historical behavior, including negative-advantage samples that suppress known failures. We show that rep

Construction-Driven Injection: Linguistically-Grounded Edit-Based Code-Mixing Fingerprints for Large Language Models

arXiv:2607.25633v1 Announce Type: cross Abstract: Large language models (LLMs) are costly intellectual assets that remain exposed to unauthorized redistribution and commercial misuse. Injected fingerp

ContractHIL-HLS: Contract-Aligned Multi-Agent Workflow with Hardware-in-the-Loop Feedback for HLS Design

arXiv:2607.25283v1 Announce Type: new Abstract: This paper presents ContractHIL-HLS, a contract-aligned multi-agent workflow for practical high-level synthesis (HLS) engineering. The workflow makes th

Cyber-Capable AI Agents: Vulnerabilities, Evaluation Containment, and Defensive Response

arXiv:2607.25379v1 Announce Type: new Abstract: Cyber-capable AI agents combine language models with tools, memory, and execution en- vironments to perform multi-step offensive-security tasks. Existin

agentsarxiv-cs-ai

Decision-Level Hijacking: Injecting Cognitive Bias into Large Language Models via Bit-Flip Attacks

arXiv:2607.25227v1 Announce Type: cross Abstract: Large Language Models (LLMs) have been widely applied in high-stakes decision-making scenarios such as corporate strategy, and users are increasingly

Do Models Fake Alignment Without Clear Consequences?

arXiv:2607.24758v1 Announce Type: new Abstract: Large language models are capable of recognizing evaluation contexts and altering their behavior to reflect evaluator expectations rather than typical d

DRIFT: Direct-Recursive Intervention-Conditioned Forecasting of ICU Physiological Trajectories

arXiv:2607.25864v1 Announce Type: new Abstract: Many time-series forecasts depend not only on prior observations but also on actions specified during the forecast period. In intensive care units (ICUs

Evaluation of Adversarial Robustness in Arabic Language Models

arXiv:2607.25814v1 Announce Type: new Abstract: The emergence of the recent outstanding capabilities of Arabic Language Models has opened doors for exposing their vulnerabilities. One of the major sec

safetyarxiv-cs-cl

Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening

arXiv:2507.11548v3 Announce Type: replace-cross Abstract: The use of publicly available generative AI systems for resume evaluation is often justified by the assumption that these tools reduce bias re

Generate Autonomous Business Insights with AI Agent and MCP Servers

Learn how Amazon Bedrock AgentCore delivers autonomous, cross-system business intelligence through configuration rather than custom code. Using pre-built MCP server connectors, fine-grained access con

agentsaws-ml-blog

Local Ai

i'll say it plainly, hermes agent desktop is the best agentic app i've used, and i'm a little mad i didn't find it sooner. it auto see the m…

i'll say it plainly, hermes agent desktop is the best agentic app i've used, and i'm a little mad i didn't find it sooner. it auto see the models i'm serving, laguna s 2.1 sitting on my dgx spark and

local-ainous-research--x

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