Search: “papers”

How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation

arXiv:2606.28358v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) aims to enhance the trustworthiness of Large Language Models (LLMs) by grounding their outputs in external docume

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Model Releases

How Far Can You Get Without a GPU? A Systematic Benchmark of Lightweight Hallucination Detection Across Question Answering, Dialogue, and Summarisation

DGX agent

arXiv:2606.29809v1 Announce Type: cross Abstract: Hallucination detection has become a pressing requirement for trustworthy AI deployment at scale. The most accurate detection methods depend on GPU-in

model-releasesarxiv-cs-ai

30 Jun 2026

Applications

HyPER-GAN: Hybrid Patch-Based Image-to-Image Translation for Real-Time Photorealism Enhancement in Game Engines

arXiv:2603.10604v3 Announce Type: replace Abstract: Generative models are increasingly used in video game engines to enhance the photorealism of rendered images for visual synthetic data generation an

applicationsarxiv-cs-cv

I-BBS: Coordinate-Free Inference of Latent Sub-Manifolds Using Random Distance Matrix Theory

model-releasesarxiv-cs-lg

arXiv:2606.29675v1 Announce Type: new Abstract: Bogomolny, Bohigas and Schmit (BBS) found that the spectrum of the pairwise distance matrix on N points sampled from a smooth d-dimensional manifold enc

IBRSteG: Learning a Generalizable Steganography Framework for 3D Gaussian Splatting

arXiv:2606.30024v1 Announce Type: cross Abstract: Recent advances in deep learning have notably improved steganographic message hiding. However, designing a generalizable steganographic approach for 3

IHDec: Divergence-Steered Contrastive Decoding for Securing Multi-Turn Instruction Hierarchies

arXiv:2606.29960v1 Announce Type: new Abstract: Large Language Models (LLMs) often fail to maintain instruction hierarchies (IH) when processing multi-source inputs with varying role-level priorities,

safetyarxiv-cs-cl

Illuminating Unified Multimodal Model for Free-form Interleaved Text-Image Generation

arXiv:2606.30054v1 Announce Type: new Abstract: The advancement of generative AI models capable of producing text and image marks a critical step forward in the realm of multimodal intelligence, parti

researcharxiv-cs-cv

Local Ai

Improvement of Robot's Simultaneous Localization and Mapping Using an Effective Transformation to Achieve Linear Model

arXiv:2606.28475v1 Announce Type: cross Abstract: Nowadays mobile robots have wide engineering applications. Simultaneous localization and mapping (SLAM) is an important task of these robots. The majo

local-aiarxiv-cs-ai

Tutorials

Informational Frustration in Neural Manifolds: Shannon Bottlenecks and the Limits of Learnability

arXiv:2606.30512v1 Announce Type: cross Abstract: Why overparameterised deep networks generalise so remarkably well remains one of the most stubborn open questions in machine learning theory. Classica

tutorialsarxiv-cs-ai

Interpretable Clustering: A Survey

arXiv:2409.00743v4 Announce Type: replace-cross Abstract: In recent years, much of the research on clustering algorithms has primarily focused on enhancing their accuracy and efficiency, frequently at

JOPP-3D: Joint Open Vocabulary Semantic Segmentation on Point Clouds and Panoramas

arXiv:2603.06168v3 Announce Type: replace Abstract: Semantic segmentation across visual modalities such as 3D point clouds and panoramic images remains a challenging task, primarily due to the scarcit

researcharxiv-cs-cv

L2D2-GS: Learning to Densify for Feedforward Dynamic Gaussian Scene Reconstruction

arXiv:2606.29374v1 Announce Type: new Abstract: High-fidelity reconstruction of dynamic urban environments is a cornerstone of autonomous driving simulation and large-scale world modeling. While 3D Ga

safetyarxiv-cs-cv

Labeling Training Data for Entity Matching Using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.28823v1 Announce Type: new Abstract: Recent large language models (LLMs) achieve strong performance on entity matching without requiring task-specific training data. However, applying these

Tutorials

LAMP: Long-Horizon Adaptive Manipulation Planning for Multi-Robot Collaboration in Cluttered Space

arXiv:2606.29358v1 Announce Type: new Abstract: Multi-robot manipulation requires jointly reasoning about contact formations, robot motions under coupled dynamics, and collision avoidance. Systematica

tutorialsarxiv-cs-ro

Lateral String Stability for Vehicle Platoons

arXiv:2606.29677v1 Announce Type: new Abstract: Connected and automated vehicle (CAV) platooning promises gains in energy efficiency and traffic throughput and, most critically, in safety. These safet

safetyarxiv-cs-ro

LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction

arXiv:2606.29407v1 Announce Type: cross Abstract: There has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE),

researcharxiv-cs-ai

Leader Reward for POMO-Based Neural Combinatorial Optimization

arXiv:2405.13947v2 Announce Type: replace Abstract: Deep neural networks based on reinforcement learning (RL) for solving combinatorial optimization (CO) problems are developing rapidly and have shown

safetyarxiv-cs-lg

Learning Deterministic Finite-State Machines from the Prefixes of a Single String is NP-Complete

arXiv:2601.12621v2 Announce Type: replace-cross Abstract: It is well known that computing a minimum deterministic finite automaton consistent with a given set of positive and negative examples is NP-h

researcharxiv-cs-lg

Learning from Mistakes: Rollout-Retrieval Lifelong Policy Learning for Autonomous Driving

arXiv:2606.30537v1 Announce Type: cross Abstract: Autonomous driving policies should be able to improve continually as deployment exposes them to increasingly diverse and long-tail traffic situations.

safetyarxiv-cs-ai

Learning to Distributedly Estimate under Partially Known Dynamics: A Covariance-Agnostic Neural Kalman Consensus Filter

arXiv:2606.28441v1 Announce Type: cross Abstract: Online latent state estimation constitutes a fundamental challenge within the artificial intelligence field, serving as a foundational tool for divers

researcharxiv-cs-ai

Learning to Route and Schedule LLMs from User Retrials via Contextual Queueing Bandits

model-releasesarxiv-cs-lg

arXiv:2602.02061v2 Announce Type: replace Abstract: Explosive demands for LLMs often cause user queries to accumulate in server queues, requiring efficient routing (query-LLM matching) and scheduling

LEIQ-Assessor: Multi-dimensional Quality Assessment of Low-light Enhanced Images via Multi-task Learning

arXiv:2606.29752v1 Announce Type: new Abstract: Low-light image enhancement algorithms (LIEAs) aim to improve the visibility of images captured under poor illumination. However, the enhancement proces

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

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

model-releasesarxiv-cs-cl

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

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

researcharxiv-cs-ai

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