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arXiv:2605.09034v1 Announce Type: new Abstract: Zeroth-order (ZO) optimization has become increasingly popular and important in fine-tuning large language models (LLMs), especially on edge devices due

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Model Releases

Acceptance Cards:A Four-Diagnostic Standard for Safe Fine-Tuning Defense Claims

DGX agent

arXiv:2605.10575v1 Announce Type: cross Abstract: Safe fine-tuning defenses are often endorsed on the basis of a held-out gap reduction, but the same reduction can come from sampling noise, subject ar

model-releasesarxiv-cs-ai

12 May 2026

Accurate Trajectory Tracking with MPCC for Flapping-Wing MAVs

arXiv:2605.06042v2 Announce Type: replace Abstract: Flapping-wing micro aerial vehicles offer quieter and safer operation than rotary-wing drones, yet achieving precise autonomous control of bird-scal

agentsarxiv-cs-ro

Ace-Skill: Bootstrapping Multimodal Agents with Prioritized and Clustered Evolution

arXiv:2605.08887v1 Announce Type: new Abstract: Self-evolving agents present a promising path toward continual adaptation by distilling task interactions into reusable knowledge artifacts. In practice

Achieving Better Local Regret Bound for Online Non-Convex Bilevel Optimization

arXiv:2602.06457v2 Announce Type: replace Abstract: Online bilevel optimization (OBO) has emerged as a powerful framework for many machine learning problems. Prior works have developed several algorit

Action-Guided Attention for Video Action Anticipation

model-releasesarxiv-cs-cv

arXiv:2603.01743v2 Announce Type: replace Abstract: Anticipating future actions in videos is challenging, as the observed frames provide only evidence of past activities, requiring the inference of la

ActivationReasoning: Logical Reasoning in Latent Activation Spaces

arXiv:2510.18184v3 Announce Type: replace-cross Abstract: Large language models (LLMs) excel at generating fluent text, but their internal reasoning remains opaque and difficult to control. Sparse aut

Tutorials

Active Learning for Gaussian Process Regression Under Self-Induced Boltzmann Weights

arXiv:2605.10654v1 Announce Type: cross Abstract: We consider the active learning problem where the goal is to learn an unknown function with low prediction error under an unknown Boltzmann distributi

tutorialsarxiv-cs-ai

Applications

Active Multiple-Prediction-Powered Inference

arXiv:2605.08429v1 Announce Type: cross Abstract: Post-deployment monitoring of healthcare AI requires statistically valid, label-efficient methods, but gold-standard labels from clinician chart revie

applicationsarxiv-cs-lg

Applications

Active-SAOOD: Active Sparsely Annotated Oriented Object Detection in Remote Sensing Images

arXiv:2605.10162v1 Announce Type: new Abstract: Reducing the annotation cost of oriented object detection in remote sensing remains a major challenge. Recently, sparse annotation has gained attention

applicationsarxiv-cs-cv

Active Tabular Augmentation via Policy-Guided Diffusion Inpainting

arXiv:2605.10315v1 Announce Type: cross Abstract: Generative tabular augmentation is appealing in data-scarce domains, yet the prevailing focus on distributional fidelity does not reliably translate i

Active Testing of Large Language Models via Approximate Neyman Allocation

arXiv:2605.10075v1 Announce Type: new Abstract: Large language models (LLMs) require reliable evaluation from pre-training to test-time scaling, making evaluation a recurring rather than one-off cost.

researcharxiv-cs-ai

ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models

model-releasesarxiv-cs-cv

arXiv:2605.08567v1 Announce Type: new Abstract: Action-conditioned world models (ACWMs) have shown strong promise for video prediction and decision-making. However, existing benchmarks are largely res

AdamFLIP: Adaptive Momentum Feedback Linearization Optimization for Hard Constrained PINN Training

arXiv:2605.08408v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a flexible framework for solving forward and inverse problems governed by partial differential equation

AdaPaD: Adaptive Parallel Deflation for PEFT with Self-Correcting Rank Discovery

arXiv:2605.10741v1 Announce Type: new Abstract: Fine-tuning large language models with LoRA requires choosing a rank r before training starts. Existing approaches either extract rank-1 components sequ

AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation

arXiv:2605.08734v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) reparameterizes a weight update as a product of two low-rank factors, but the Jacobian J_{G} of the generator mapping the f

Adaptive 3D Convolution for Remote Sensing Image Fusion

arXiv:2605.09455v1 Announce Type: new Abstract: Remote sensing image fusion aims to create a high-resolution multi/hyper-spectral image from a high-resolution image with limited spectral information a

researcharxiv-cs-cv

Adaptive Action Chunking via Multi-Chunk Q Value Estimation

arXiv:2605.10044v1 Announce Type: cross Abstract: Action chunking emerged as a pivotal technique in imitation learning, enabling policies to predict cohesive action sequences rather than single action

Adaptive Context Matters: Towards Provable Multi-Modality Guidance for Super-Resolution

arXiv:2605.10470v1 Announce Type: new Abstract: Super-resolution (SR) is a severely ill-posed problem with inherent ambiguity, as widely recognized in both empirical and theoretical studies. Although

safetyarxiv-cs-cv

Adaptive Data Harvesting for Efficient Neural Network Learning with Universal Constraints

arXiv:2605.09707v1 Announce Type: cross Abstract: Training neural networks to satisfy universal constraints over continuous domains poses unique challenges. Common examples include Lyapunov Neural Net

Applications

Adaptive digital twins for predictive decision-making: Online Bayesian learning of transition dynamics

arXiv:2512.13919v2 Announce Type: replace Abstract: This work shows how adaptivity can enhance value realization of digital twins in civil engineering. We focus on adapting the state transition models

applicationsarxiv-cs-lg

Adaptive DNN Partitioning and Offloading in Heterogeneous Edge-Cloud Continuum

arXiv:2605.09623v1 Announce Type: cross Abstract: In recent years, the use of artificial intelligence on resource-constrained IoT devices has grown significantly. However, existing approaches to DNN p

researcharxiv-cs-ai

Adaptive Memory Momentum via a Model-Based Framework for Deep Learning Optimization

arXiv:2510.04988v3 Announce Type: replace Abstract: The vast majority of modern deep learning models are trained with momentum-based first-order optimizers. The momentum term governs the optimizer's m

Adaptive Multi-view Graph Contrastive Learning via Fractional-order Neural Diffusion Networks

arXiv:2511.06216v4 Announce Type: replace Abstract: Graph contrastive learning (GCL) learns node and graph representations by contrasting multiple views of the same graph. Existing methods typically r

AdaptSplat: Adapting Vision Foundation Models for Feed-Forward 3D Gaussian Splatting

arXiv:2605.10239v1 Announce Type: new Abstract: This work explores a simple yet powerful lightweight adapter design for feed-forward 3D Gaussian Splatting (3DGS). Existing methods typically apply comp

researcharxiv-cs-cv

Local Ai

AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning

arXiv:2410.13181v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have been remarkable. Users face a choice between using cloud-based LLMs for generation quality

local-aiarxiv-cs-cl

Additive Atomic Forests for Symbolic Function and Antiderivative Discovery

arXiv:2605.08130v1 Announce Type: new Abstract: We present a framework for the simultaneous symbolic recovery of a function and its antiderivative from data. The framework rests on three ideas. First,

Advanced Tumor Segmentation in PET/CT Imaging: A Training Strategy Study with nnU-Net for AutoPET III

arXiv:2605.08161v1 Announce Type: new Abstract: Tumor segmentation in whole-body PET/CT imaging is crucial for precise disease evaluation and treatment planning. However, it remains challenging due to

researcharxiv-cs-cv

Advancing AI for materials with MatterSim: experimental synthesis, faster simulation, and multi-task models

researchmicrosoft-research

MatterSim is expanding what AI can do for materials science—from faster large-scale simulations to MatterSim-MT, a new multi-task model for simulating properties beyond potential energy surfaces alone

Adversarial Attacks Against MLLMs via Progressive Resolution Processing and Adaptive Feature Alignment

arXiv:2605.09902v1 Announce Type: new Abstract: Adversarial perturbations can mislead Multimodal Large Language Models (MLLMs) recognize a benign image as a specific target object, posing serious risk

safetyarxiv-cs-cv

Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates

arXiv:2605.09337v1 Announce Type: new Abstract: We propose FAR-SIGN (Fully Asynchronous Robust optimization via SIGNed directional projections) for adversary-resilient learning in parameter-server--wo

Industry

AfD bei 28%, inzwischen hat sich der Abstand zur Union (22%) auf 6 Punkte vergrößert. Gleichzeitig sinkt auch das Verständnis für die 'Brand…

AfD bei 28%, inzwischen hat sich der Abstand zur Union (22%) auf 6 Punkte vergrößert. Gleichzeitig sinkt auch das Verständnis für die 'Brandmauer'. Deutschland will den Wandel - wir sind dafür bereit.

industryelon-musk--x

Affine Tracing: A New Paradigm for Probabilistic Linear Solvers

arXiv:2605.10566v1 Announce Type: cross Abstract: Probabilistic linear solvers (PLSs) return probability distributions that quantify uncertainty due to limited computation in the solution of linear sy

Industry

After seeing the new OpenAI and Thinking Machines voice APIs, I did finally order a Reachy. Way more excited to talk to this thing than a Go…

After seeing the new OpenAI and Thinking Machines voice APIs, I did finally order a Reachy. Way more excited to talk to this thing than a Google puck Reachy is mad, but RAM costs + tariffs are forcing

industryclem-delangue--x

Hardware

After studying 300 Leetcode Hards, solving every Jane Street puzzle from the Dwarkesh ads, and watching one Horace He lecture, he finally la…

After studying 300 Leetcode Hards, solving every Jane Street puzzle from the Dwarkesh ads, and watching one Horace He lecture, he finally landed the $400k annualized Jane Street internship. Unfortunat

hardwaredylan-patel--x

Agent-First Tool API: A Semantic Interface Paradigm for Enterprise AI Agent Systems

arXiv:2605.10555v1 Announce Type: new Abstract: As AI agents transition from research prototypes to enterprise production systems, the tool interfaces they consume remain rooted in human-oriented CRUD

Agent-Omit: Adaptive Context Omission for Efficient LLM Agents

arXiv:2602.04284v2 Announce Type: replace Abstract: Managing agent context (e.g., thought and observation) during multi-turn agent-environment interactions is an emerging strategy to improve agent eff

Agent-Sentry: Bounding LLM Agents via Execution Provenance

arXiv:2603.22868v2 Announce Type: replace-cross Abstract: Agentic computing systems, while immensely capable, raise serious security, privacy, and safety concerns. A key issue is that the full set of

Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values

arXiv:2605.10365v1 Announce Type: new Abstract: Autonomous agents have rapidly matured as task executors and seen widespread deployment via harnesses such as OpenClaw. Safety concerns have rightly dra

Local Ai

Agent-X: Full Pipeline Acceleration of On-device AI Agents

arXiv:2605.10380v1 Announce Type: new Abstract: LLM-based agents deliver state-of-the-art performance across tasks but incur high end-to-end latency on edge devices. We introduce Agent-X, a software-o

local-aiarxiv-cs-ai

AgentCollabBench: Diagnosing When Good Agents Make Bad Collaborators

arXiv:2605.08647v1 Announce Type: cross Abstract: Multi-agent systems achieve state-of-the-art outcomes through peer collaboration. However, when an agent in the pipeline silently drops a constraint,

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems

arXiv:2605.08715v1 Announce Type: cross Abstract: LLM-based multi-agent systems are increasingly deployed on long-horizon tasks, but a single decisive error is often accepted by downstream agents and

Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery

arXiv:2605.08956v1 Announce Type: new Abstract: A growing body of work pursues AI scientists capable of end-to-end autonomous scientific discovery. This position paper argues that although they alread

Agentic MIP Research: Accelerated Constraint Handler Generation

arXiv:2605.09186v1 Announce Type: new Abstract: Mixed-integer programming (MIP) research is both mathematically sophisticated and engineering-intensive: testing an algorithmic hypothesis within a bran

Agentic Performance at the Edge: Insights from Benchmarking

arXiv:2605.10384v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) is a natural fit for Internet of Things (IoT) and edge systems, but edge deployments are often constrained to model

Agentic SOC startup Exaforce closes 125M round at reported 725M valuation

Agentic security operations startup Exaforce Inc. today announced that it has raised 125 million in new funding to scale up its AI-driven security operations platform and expand its real-time threat r

agentssiliconangle

AgentPSO: Evolving Agent Reasoning Skill via Multi-agent Particle Swarm Optimization

arXiv:2605.08704v1 Announce Type: new Abstract: Multi-agent reasoning has shown promise for improving the problem-solving ability of large language models by allowing multiple agents to explore divers

AgentReview: Exploring Peer Review Dynamics with LLM Agents

arXiv:2406.12708v3 Announce Type: replace Abstract: Peer review is fundamental to the integrity and advancement of scientific publication. Traditional methods of peer review analyses often rely on exp

safetyarxiv-cs-cl