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arXiv:2510.07343v3 Announce Type: replace-cross Abstract: Diffusion Posterior Sampling (DPS) provides a principled Bayesian approach to inverse problems by sampling from p(x_0 mid y). While posterior

local-aiarxiv-cs-ai

Locality Matters for Training-Free Audio Token Compression in Audio-Language Models

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arXiv:2605.25179v1 Announce Type: new Abstract: Audio-language models (ALMs) are increasingly used for audio captioning, question answering, and open-ended audio understanding, but their inference cos

safetyarxiv-cs-cl

26 May 2026

Local Ai

Localization then Neutralization: Gradient-guided Token Suppression against Visual Prompt Injection Attack

arXiv:2605.25194v1 Announce Type: new Abstract: Adversarial images pose a severe security threat to multimodal large language models through prompt injection. Existing defenses largely lack a principl

local-aiarxiv-cs-lg

Logic-Guided Socially-aware Robot Navigation World Model

arXiv:2510.23509v2 Announce Type: replace Abstract: Social robot navigation increasingly relies on large language models for reasoning, path planning, and enabling movement in dynamic human spaces. Ho

researcharxiv-cs-ro

Logic-Guided Vector Fields for Constrained Generative Modeling

arXiv:2602.02009v2 Announce Type: replace Abstract: Neuro-symbolic systems aim to combine the expressive structure of symbolic logic with the flexibility of neural learning; yet, generative models typ

researcharxiv-cs-lg

Looped Diffusion Language Models

arXiv:2605.26106v1 Announce Type: new Abstract: Masked diffusion models (MDMs) have emerged as a promising alternative to autoregressive models for language modeling, yet the effective design of trans

Loosely Coupled Factor Graph Optimization for Pseudolite-Augmented Navigation

arXiv:2605.24980v1 Announce Type: new Abstract: In Global Navigation Satellite System (GNSS)-degraded environments, pseudolites (PLs) provide additional signal sources to enhance positioning performan

researcharxiv-cs-ro

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling

arXiv:2605.23957v1 Announce Type: new Abstract: Learning-assisted hyper-heuristics can select among dispatching rules while preserving the feasibility and interpretability of constructive Job Shop Sch

LRDDv3: High-Resolution Long-Range Drone Detection Dataset with Range Information and Thermal Data

arXiv:2605.25942v1 Announce Type: cross Abstract: Unmanned Aerial Vehicles (UAVs) have quickly become common in various airspaces, representing a wide range of applications from recreation flying to c

researcharxiv-cs-ro

LWM-CDE: A Representation Space for Wireless Data Reasoning and Transferability

arXiv:2605.24077v1 Announce Type: cross Abstract: Machine learning deployments in real-world wireless communication tasks face significant generalization challenges due to location and environment-spe

applicationsarxiv-cs-lg

M^3-Verse: A 'Spot the Difference' Challenge for Large Multimodal Models

arXiv:2512.18735v2 Announce Type: replace-cross Abstract: Modern Large Multimodal Models (LMMs) have demonstrated extraordinary ability in static image and single-state spatial-temporal understanding.

Machine Intelligence that Understands Visual and Linguistic Information and Interacts with Humans and Environments

arXiv:2605.24020v1 Announce Type: cross Abstract: Advancements at the intersection of computer vision and natural language processing are crucial for applications like assistive tech, multimedia query

Machine Learning Multiscale Interactions

arXiv:2605.25710v1 Announce Type: cross Abstract: Realistic physical systems are characterised by emergent interactions across multiple length and time scales, posing a significant challenge for predi

researcharxiv-cs-lg

Machine Psychometrics: A Mathematical Psychology of Artificial Intelligence

arXiv:2605.23952v1 Announce Type: new Abstract: Artificial agents now generate behavior rich enough to invite trust, surprise, and concern, yet our evaluation tools still privilege capability scores o

MAGIC: Multimodal Alignment & Grounding-aware Instruction Coreset for Vision-Language Models

arXiv:2605.26004v1 Announce Type: cross Abstract: Instruction tuning of large vision-language models (LVLMs) increasingly depends on massive multimodal corpora, yet these datasets contain samples with

safetyarxiv-cs-cl

Manifold-Constrained MPPI: Real-Time Sampling-Based Control Under Hard Constraints

arXiv:2605.24813v1 Announce Type: new Abstract: Sampling-based model predictive control methods, such as Model Predictive Path Integral (MPPI), offer derivative-free optimization and robustness in com

applicationsarxiv-cs-ro

MAPLE: Multi-State Aggregated Policy Evaluation for AlphaZero in Imperfect-Information Games

arXiv:2605.24139v1 Announce Type: new Abstract: Imperfect-information games (IIGs) are challenging, as players must make decisions without fully observing the true game state. While AlphaZero has achi

Mapping the Schedule x Bit-Width Boundary in Sub-100M Quantisation-Aware Training

arXiv:2605.25966v1 Announce Type: cross Abstract: We test whether the optimal learning-rate schedule depends on bit-width during from-initialisation quantisation-aware training (QAT) for sub-100M deco

researcharxiv-cs-cl

Market Regime Council for Dynamic Credit Assignment in Multi-Agent LLM Decision Systems

arXiv:2605.24490v1 Announce Type: new Abstract: Multi-agent LLM decision systems for portfolio management still lack a principled way to assign credit across specialist agents, remain vulnerable to co

MARS: Margin and Semantic-Aware Data Augmentation for Reward Modeling

arXiv:2602.17658v2 Announce Type: replace-cross Abstract: Reward modeling is central to alignment pipelines such as RLHF, RLAIF, and PPO-based policy optimization, yet its reliability is constrained b

MASt3R-Nav: WayPixel Navigation in Relative 3D Maps

arXiv:2605.24111v1 Announce Type: cross Abstract: Visual navigation ability is strongly tied to its underlying representation of the world. Unlike classical 3D maps that require globally-consistent ge

applicationsarxiv-cs-ai

Hardware

MathOptAI.jl: Embed trained machine learning predictors into JuMP models

arXiv:2507.03159v2 Announce Type: replace Abstract: We present exttt{MathOptAI.jl}, an open-source Julia library for embedding trained machine learning predictors into a JuMP model. exttt{MathOptAI.jl

hardwarearxiv-cs-lg

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models

arXiv:2605.25342v1 Announce Type: new Abstract: Aligning large language models (LLMs) with diverse and multifaceted user preferences is a fundamental challenge in personalized AI systems. Existing mul

safetyarxiv-cs-cl

MCPXKIT: The Unified Toolkit for Analyzing Model Context Protocol Security

arXiv:2508.12538v2 Announce Type: replace-cross Abstract: The Model Context Protocol (MCP) has emerged as a universal standard that enables AI agents to seamlessly connect with external tools, signifi

MDGMIX: Boundary-Aware Subgraph Mixing for Multi-Domain Graph Pre-Training

arXiv:2605.25771v1 Announce Type: cross Abstract: Multi-domain graph pre-training is a crucial step in constructing foundational graph models with cross-domain generalization capabilities. However, ex

MDIA: A Multi-Agent Diagnostic Intelligence Pipeline on HealthBench Professional

arXiv:2605.24699v1 Announce Type: new Abstract: Most reported gains on agentic-LLM clinical benchmarks are often attributed to prompt engineering, yet our results suggest that larger improvements can

Tutorials

Mean-Shift PCA by Knockoff Mean

arXiv:2605.25460v1 Announce Type: cross Abstract: Removing noise is difficult, but adding noise is easy. In this work, we show how to eliminate mean-shift noisy components from PCA by deliberately int

tutorialsarxiv-cs-lg

Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework

arXiv:2605.24661v1 Announce Type: new Abstract: LLMs have achieved remarkable success in complex reasoning tasks, yet current evaluation approaches predominantly rely on final-answer correctness, offe

Measuring the Depth of LLM Unlearning via Activation Patching

arXiv:2605.24614v1 Announce Type: cross Abstract: Large language model (LLM) unlearning has emerged as a crucial post-hoc mechanism for privacy protection and AI safety, yet auditing whether target kn

MEDAL: Manifold Embedding Distillation via Autoencoder Learning

arXiv:2605.24244v1 Announce Type: cross Abstract: Low-dimensional embeddings are widely used as visual summaries of high-dimensional data and to enable downstream scientific discoveries. Yet, popular

MedBeads: An Agent-Native, Immutable Data Substrate for Trustworthy Medical AI

arXiv:2602.01086v2 Announce Type: replace Abstract: Background: As of 2026, Large Language Models (LLMs) demonstrate expert-level medical knowledge. However, deploying them as autonomous 'Clinical Age

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification

arXiv:2605.24961v1 Announce Type: new Abstract: Medical time series are central to healthcare, enabling continuous monitoring and supporting timely clinical decisions. Despite recent progress, existin

applicationsarxiv-cs-lg

Membership Inference Attacks on Tokenizers of Large Language Models

arXiv:2510.05699v4 Announce Type: replace-cross Abstract: Membership inference attacks (MIAs) are widely used to assess the privacy risks associated with machine learning models. However, when these a

applicationsarxiv-cs-ai

MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing

arXiv:2605.23986v1 Announce Type: cross Abstract: Memory is a fundamental component for enabling long-context LLM agents, supporting persistent state across interactions through a continuous serve-and

MEMOR-E: In-Context and Fine-Tuned LLM Personalization for Alzheimer's Assistive Robotics

arXiv:2605.23941v1 Announce Type: new Abstract: Alzheimer's disease is a neurodegenerative disorder marked by progressive declines in memory and language that reduce independence in daily life, motiva

Memory-Induced Tool-Drift in LLM Agents

arXiv:2605.24941v1 Announce Type: cross Abstract: Modern LLM agents combine long-term memory for personalization with tool-calling interfaces for taking actions in the world -- a combination underpinn

MemSkill: Learning and Evolving Memory Skills for Self-Evolving Agents

arXiv:2602.02474v2 Announce Type: replace-cross Abstract: Most Large Language Model (LLM) agent memory systems rely on a small set of static, hand-designed operations for extracting memory. These fixe

Merge-Bench: Resolve Merge Conflicts with Large Language Models

arXiv:2605.25890v1 Announce Type: new Abstract: This paper applies machine learning to the difficult and important task of version control merging. (1) We constructed a dataset, Merge-Bench, of 7938 r

Message-Passing GNNs Fail to Approximate Sparse Triangular Factorizations

arXiv:2502.01397v3 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have been proposed as a tool for learning sparse matrix preconditioners, which are key components in accelerating

applicationsarxiv-cs-ai

Meta-Agent: From Task Descriptions to Verified Multi-Agent Systems

arXiv:2605.25233v1 Announce Type: new Abstract: AI agents are increasingly used to solve complex, multi-step tasks, but existing multi-agent frameworks remain brittle as workflows grow in scale and de

Meta-Engineering Harnesses for AI-Native Software Production: A Contract-Driven Adversarial Verification Architecture with Early Deployment Report

arXiv:2605.25665v1 Announce Type: cross Abstract: AI-native software development is often evaluated at the level of individual models, prompts, or generated artifacts. This framing is insufficient for

Meta-Soft: Leveraging Composable Meta-Tokens for Context-Preserving KV Cache Compression

arXiv:2605.22337v2 Announce Type: replace Abstract: The KV cache used in large language models has linearly growing time complexity, so LLMs face memory blow-up and reduced decoding efficiency when th

Metacognition Should Be the Scientific Framework for Bounded and Effective Self-Governance in Generative AI

arXiv:2605.23981v1 Announce Type: cross Abstract: Generative AI research increasingly confronts a shared problem: systems must sustain yet govern their own generative activity when uncertainty is high

Methodology for Creating a Clinically Verified Dermoscopic Image Dataset

arXiv:2605.25168v1 Announce Type: cross Abstract: This study presents a methodology for constructing a clinically verified dataset of dermatoscopic images for medical informatics research. The relevan

Methods for Formal Verification of Agent Skills: Three Layers Toward a Mechanically Checkable Capability-Containment Proof

arXiv:2605.23951v1 Announce Type: new Abstract: The companion paper introduced a four-level verification lattice on agent-skill manifests (unverified, declared, tested, formal) and left the top level

Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data

arXiv:2605.25004v1 Announce Type: cross Abstract: Inferring network-wide traffic states from sparse observations with high accuracy and trustworthy uncertainty quantification is essential for intellig

MGVQ: Synergizing Multi-dimensional Sensitivity-Aware and Gradient-Hessian Fusion for Vector Quantization

arXiv:2605.24019v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) achieve outstanding performance, yet their huge model size severely hinders deployment on edge devices with limited reso

researcharxiv-cs-lg

Micro-Swarm Locomotion Optimization in Dynamic Flow using Multi-Objective Multi-Agent Reinforcement Learning

arXiv:2605.25025v1 Announce Type: new Abstract: Coordinating micro-robotic swarms in physiologically realistic, time-dependent fluid environments remains an unsolved challenge for biomedical and envir

safetyarxiv-cs-ro