Search: “papers”

LogiCo: A Unified Framework for Logical and Structural Anomaly Detection

arXiv:2606.28688v1 Announce Type: new Abstract: Current anomaly detection methods primarily focus on structural anomalies, while paying insufficient attention to anomalies that violate logical constra

researcharxiv-cs-cv

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MaDI-Bench: An End-to-End Data Integration Benchmark

DGX agent

arXiv:2606.30371v1 Announce Type: cross Abstract: Data integration combines heterogeneous data sets into a single, coherent representation. Data integration involves a sequence of interdependent tasks

model-releasesarxiv-cs-cl

30 Jun 2026

mamabench and mamaretrieval: Benchmarks for Evaluating Medical Retrieval-Augmented Generation in Maternal, Neonatal, and Reproductive Health

model-releasesarxiv-cs-cl

arXiv:2606.29467v1 Announce Type: new Abstract: Medical question-answering benchmarks rarely cover the maternal, neonatal, child, and reproductive-health questions a nurse-midwife asks, and, to our kn

ManimAgent: Self-Evolving Multimodal Agents for Visual Education

arXiv:2606.30296v1 Announce Type: new Abstract: Multi-round reflection lets agents built on large language models recover from failures within a single task, but each task remains an isolated episode:

Masked Diffusion Decoding as x-Prediction Flow

arXiv:2606.29066v1 Announce Type: new Abstract: Masked diffusion language models (MDLMs) generate text by iteratively unmasking tokens, but their standard decoder reduces each step to a binary action:

safetyarxiv-cs-cl

MAVIN: Multi-Shot Audio-Visual Generation with Narrative Control

arXiv:2606.29473v1 Announce Type: new Abstract: While recent generative models produce high-fidelity videos, they struggle with the complex narrative control required for coherent multi-shot audio-vis

agentsarxiv-cs-cv

MCP Server Architecture Patterns for LLM-Integrated Applications

arXiv:2606.30317v1 Announce Type: cross Abstract: The Model Context Protocol (MCP), introduced by Anthropic in November 2024, defines a standardized interface for connecting large language models (LLM

MedDiffuseMix: Preserving Diagnostic Evidence with Saliency-Aware Diffusion Medical Image Data Augmentatio

arXiv:2606.28419v1 Announce Type: cross Abstract: Limited data availability, class imbalance, and domain variability remain major barriers to reliable medical image classification. Conventional augmen

Memory as an Attack Surface in LLM Agents: A Study on Multiple-Choice Question Answering

arXiv:2606.29030v1 Announce Type: new Abstract: AI agents extend conventional large language model (LLM) applications by integrating language understanding with task execution, external tool use, and

MESA: Prioritizing Vulnerable Communication Channels for Securing Multi-Agent Systems

arXiv:2606.30602v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used to automate complex, distributed workflows. However, their inter-agent communication channels introduc

Local Ai

MF-UAVPose6D: A Model-Free Monocular 6-DoF Pose Estimation Framework for Fixed-Wing UAVs

arXiv:2606.29697v1 Announce Type: new Abstract: For uncrewed aerial vehicles (UAVs), estimating six-degree-of-freedom (6-DoF) poses is essential for airspace situational awareness, target tracking, an

local-aiarxiv-cs-cv

MOAR Planner: Multi-Objective and Adaptive Risk-Aware Path Planning for Infrastructure Inspection with a UAV

arXiv:2606.30575v1 Announce Type: new Abstract: The problem of autonomous navigation for UAV inspection remains challenging as it requires effectively navigating in close proximity to obstacles, while

safetyarxiv-cs-ro

Model Merging to Evolution: Parameter Space Exploration for Expert Models

arXiv:2606.28373v1 Announce Type: cross Abstract: Model merging integrates the capabilities of multiple expert models to create strong models for multiple tasks without additional training, thereby re

Model Predictive Current Control with Harmonic Correction for Single-Phase AC-DC EV Charging

arXiv:2606.30397v1 Announce Type: cross Abstract: The increasing integration of Electric Vehicles (EVs) has imposed a growing harmonic challenge on the power grid. For AC/DC Power Factor Correction (P

Monte Carlo Energy Aggregation for Mobile 3D Gaussian Splatting

arXiv:2606.30017v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting have demonstrated unprecedented success in novel view synthesis. However, the substantial inference and storage

MTD-Map: Single-Stage Long-Term LiDAR Map Maintenance Framework via Mixture Transition Distribution

arXiv:2606.29469v1 Announce Type: new Abstract: While robust map maintenance has advanced significantly, existing studies have focused on specific tasks, especially dynamic object removal or change de

researcharxiv-cs-ro

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks

arXiv:2606.28339v1 Announce Type: cross Abstract: Industrial 6G networks require ultra-reliable, low-latency, and energy-efficient connectivity in dynamic and blockage-prone environments, where conven

Multi-Agent Route Planning as a QUBO Problem

model-releasesarxiv-cs-ro

arXiv:2602.07913v2 Announce Type: replace Abstract: Multi-Agent Route Planning considers selecting vehicles, each associated with a single predefined route, such that route-level coverage utility is m

Multimodal Graph RAG for Long-range Visually Rich Document Understanding

arXiv:2606.28780v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are widely applied to visual document understanding. However, comprehending long documents remains an issue b

Multimodal Large Language Model driven Radiology Report Generation with Clinical Knowledge Enhancement

arXiv:2403.06728v2 Announce Type: replace Abstract: Radiology report generation (RRG) has attracted significant attention due to its potential to reduce the workload of radiologists. The performance o

safetyarxiv-cs-cv

MUSE: Unlocking Timestep as Native Task Steering for One-Step Dense Prediction

arXiv:2606.30370v1 Announce Type: new Abstract: Monocular dense prediction has recently seen remarkable success by repurposing pre-trained diffusion models. This opens a promising yet challenging aven

Neural Procedural Memory: Empowering LLM Agents with Implicit Activation Steering

arXiv:2606.29824v1 Announce Type: cross Abstract: While Large Language Models (LLMs) excel as static solvers, transforming them into autonomous agents remains challenging. This transition requires con

Node-to-Neighborhood Semantic Consistency: Text-Topology Alignment for TAGs Anomaly Detection

arXiv:2606.30009v1 Announce Type: new Abstract: Graph anomaly detection (GAD) on text-attributed graphs (TAGs) is vital for applications such as fraud detection and academic integrity verification. Ex

safetyarxiv-cs-cl

OGM-CBF: Occupancy Grid Map-based Control Barrier Function for Safe Mobile Robot Control with Memory of out of View Obstacles

arXiv:2405.10703v4 Announce Type: replace Abstract: Safe control in unknown environments is a key challenge in mobile robotics. Control Barrier Functions (CBFs) provide a principled framework for guar

safetyarxiv-cs-ro

On the Vulnerability of Parameter-Level Defenses to Model Merging

arXiv:2606.30360v1 Announce Type: cross Abstract: The training-free integration of expert models via model merging has exposed significant security risks, enabling free-riders to combine specialized m

Applications

Pairwise Comparisons without Stochastic Transitivity: Model, Theory and Applications

arXiv:2501.07437v3 Announce Type: replace-cross Abstract: Most statistical models for pairwise comparisons, including the Bradley-Terry (BT) and Thurstone models and many extensions, make a relatively

applicationsarxiv-cs-lg

PASTA: A Paraphrasing And Self-Training Approach for Knowledge Updating in LLMs

arXiv:2606.28898v1 Announce Type: new Abstract: Knowledge updating in pre-trained Large Language Models (LLMs) remains an important challenge. While continual training provides a potential avenue for

researcharxiv-cs-cl

PLAA: Packet-level Adversarial Attacks in Network Traffic Detection

arXiv:2606.28439v1 Announce Type: cross Abstract: Deep neural networks (DNNs) are widely applied in Network-based Intrusion Detection System (NIDS) due to their high accuracy. However, DNNs are highly

PLOT: Pseudo-Labeling via Object Tracking for Monocular 3D Object Detection

arXiv:2507.02393v2 Announce Type: replace Abstract: Monocular 3D object detection is crucial for scalable perception across fields like autonomous driving, robotics, and surveillance. However, progres

agentsarxiv-cs-cv

Poller: Are LLMs Suitable for Evaluating the Poetry Understanding Task?

arXiv:2606.30556v1 Announce Type: new Abstract: Traditional automatic evaluation methods have been shown to be unsuitable for modern Chinese poetry because of the distinct nature of this literary genr

researcharxiv-cs-cl

Pose-Based Fall Detection System: Efficient Monitoring on Standard CPUs

arXiv:2503.19501v2 Announce Type: replace-cross Abstract: Falls among elderly residents in assisted living homes pose significant health risks, often leading to injuries and a decreased quality of lif

safetyarxiv-cs-ai

Position: RL Researchers Need to Distinguish Between Solving Simulators and Using Simulators as a Proxy

model-releasesarxiv-cs-lg

arXiv:2606.28433v1 Announce Type: new Abstract: One goal in reinforcement learning (RL) research is to understand general-purpose sequential decision-making, using benchmark simulators as a proxy for

Predicting Effects, Missing Distributions: Evaluating LLMs as Human Behavior Simulators in Operations Management

arXiv:2510.03310v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to simulate human behavior in business, economics, and the social sciences, offering a low-

Preventing Error Propagation in Multi-Agent AI through Runtime Monitoring

arXiv:2606.29026v1 Announce Type: new Abstract: Multi-agent AI systems can improve answer selection by allowing different language models to exchange reasoning traces, revise initial predictions, and

Priced Motion Through Optimal Faces: A Normal-Fan Geometry for Non-Stationary Adversarial MDPs

arXiv:2606.29092v1 Announce Type: cross Abstract: In a changing decision problem, standard dynamic-regret analyses have often equated the cost of non-stationarity to how far loss moves. However, it is

safetyarxiv-cs-ai

Projected Exploitability Descent for Nash Equilibrium Computation in Multiplayer Imperfect-Information Games

arXiv:2606.29169v1 Announce Type: cross Abstract: Many important games have more than two players and imperfect information. Existing approaches for computing Nash equilibrium, the central game-theore

RBE-Flow: Recurrent Bayesian Estimation on Feature Manifolds for Cross-Modal Registration

arXiv:2606.30492v1 Announce Type: new Abstract: Cross-modal image registration is essential for multi-sensor perception but remains fundamentally challenging due to severe non-linear radiometric discr

researcharxiv-cs-cv

Real-Time Compliance and Position Control of a Hyper-redundant Soft Robotic Arm

arXiv:2606.29731v1 Announce Type: new Abstract: Robots working in unstructured or partially unobservable environments must combine accurate motion with physical compliance that can passively correct c

researcharxiv-cs-ro

Reconsidering Overthinking: Penalizing Internal and External Redundancy in CoT Reasoning

arXiv:2508.02178v3 Announce Type: replace Abstract: Large reasoning models (LRMs) often exhibit overthinking, producing verbose Chain-of-Thought (CoT) traces that increase inference cost and obscure t

RefAlign: Representation Alignment for Reference-to-Video Generation

arXiv:2603.25743v2 Announce Type: replace Abstract: Reference-to-video (R2V) generation is a controllable video synthesis paradigm that constrains the generation process using both text prompts and re

Local Ai

Relevance Is Not Permission: Warranted Attention for Value Contributions

arXiv:2606.30139v1 Announce Type: new Abstract: Relevance is not permission. Attention lets a model read key-value items related to the current query, but it does not guarantee that the value contribu

local-aiarxiv-cs-ai

Applications

Representation Learning for Equivariant Inference with Guarantees

arXiv:2505.19809v3 Announce Type: replace-cross Abstract: In many real-world applications of regression, conditional probability estimation, and uncertainty quantification, exploiting symmetries roote

applicationsarxiv-cs-ai

Residual-Guided Dictionary Learning for Spectrally Accurate Koopman Approximation

model-releasesarxiv-cs-lg

arXiv:2606.29083v1 Announce Type: cross Abstract: Koopman theory promises linear structure in nonlinear dynamics, but numerical Koopman spectra are easy to compute and hard to trust. A finite EDMD mat

Resolution Thresholds in VLM Detection of Harmful ASCII Art Across Construction Modes and Languages

arXiv:2606.29649v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) are increasingly deployed as content moderation tools, yet they remain vulnerable to jailbreak attacks in which harm

safetyarxiv-cs-cl

RetrDex: Efficient Object Retrieval in Cluttered Scenes with a Dexterous Hand

arXiv:2502.18423v3 Announce Type: replace Abstract: Retrieving objects buried beneath clutter is both challenging and time-consuming, as complex support relationships make manipulation particularly di

safetyarxiv-cs-ro

Reward-Free Code Alignment from Pretrained or Fine-Tuned LLM: Unpacking the Trade-offs for Code Generation

arXiv:2606.28998v1 Announce Type: cross Abstract: Large Language Model (LLM) alignment trains an LLM using preference data to produce outputs that better meet established quality standards. While LLM

Hardware

Robust and Efficient Monocular 3D Gaussian SLAM for Kilometer-Scale Outdoor Scenes

arXiv:2606.30436v1 Announce Type: new Abstract: Scaling monocular 3D Gaussian Splatting (3DGS) SLAM to kilometer-level outdoor environments poses two tightly coupled challenges: fragile long-term pose

hardwarearxiv-cs-cv

Robust Strategic Classification under Decision-Dependent Cost Uncertainty

arXiv:2606.30136v1 Announce Type: new Abstract: Humans facing algorithmic decision systems have been found to ``game'' them by altering their input data (at a cost to them) in order to favorably chang

safetyarxiv-cs-lg