Search: “framework”

arXiv:2606.29636v1 Announce Type: cross Abstract: An important task in quantum computing is unitary circuit synthesis compatible with physical hardware constraints. This problem has a natural hybrid s

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Local Ai

LLM-Ideoplasticity: Measuring Ideological Plasticity in the Political Behavior of LLMs as a Context-Conditioned Distribution

DGX agent

arXiv:2606.28335v1 Announce Type: cross Abstract: We argue, with systematic empirical evidence, that a large language model's political ideology is not a fixed point, but a conditional distribution P(

local-aiarxiv-cs-ai

30 Jun 2026

LLMography: Transforming Human-AI Conversations into Traceability, Oversight, and Auditability Indicators

arXiv:2606.29437v1 Announce Type: cross Abstract: The growing use of Large Language Models (LLMs) in education, software engineering, academic writing, and technical documentation raises a key questio

applicationsarxiv-cs-ai

LoGSAM: Parameter-Efficient Cross-Modal Grounding for MRI Segmentation

arXiv:2603.17576v3 Announce Type: replace Abstract: Precise localization and delineation of brain tumors using magnetic resonance imaging (MRI) are essential for planning therapy and guiding surgical

LoRAShield: Data-Free Editing Alignment for Secure Personalized LoRA Sharing

arXiv:2507.07056v2 Announce Type: replace-cross Abstract: The proliferation of Low-Rank Adaptation (LoRA) models has democratized personalized text-to-image generation, enabling users to share lightwe

safetyarxiv-cs-lg

Local Ai

Low-cost concept-based localized explanations: How far can we get with training-free approaches?

arXiv:2606.29069v1 Announce Type: new Abstract: Concept-based Explainable AI (C-XAI) seeks human-understandable explanations grounded in semantic concepts, yet validation is limited by the scarcity of

local-aiarxiv-cs-ai

M^3 QuestionIng: Multi-modal Multi-span Medical Question Answering

arXiv:2606.28329v1 Announce Type: cross Abstract: The growing adoption of AI in healthcare, particularly in preventive care, highlights the critical need for accessibility and precision in Medical Que

applicationsarxiv-cs-ai

MALOQ: Massively Accelerated Learning of Operators for Quantum Transport

arXiv:2606.28911v1 Announce Type: new Abstract: Machine-learned (ML) operator models can be trained to predict density functional theory (DFT) Hamiltonian/density matrices at significantly reduced com

researcharxiv-cs-lg

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

MATCH: Modulating Attention via In-Context Retrieval for Long-Context Transformers

arXiv:2606.29844v1 Announce Type: cross Abstract: The quadratic computational cost of traditional attention mechanisms poses a major bottleneck to the scalability and practical deployment of large lan

applicationsarxiv-cs-ai

Agents

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

McMg: A Learned Phase-Space Multi-channel Multigrid Preconditioner for Helmholtz Equation

arXiv:2606.30495v1 Announce Type: cross Abstract: Solving heterogeneous Helmholtz equations at high wavenumbers remains challenging because the discretized operator is indefinite, pollution degrades p

MedEvoEval: Evaluating Continual Evolution of Doctor Agents through Simulated Clinical Episodes

arXiv:2606.28900v1 Announce Type: new Abstract: Doctor agents are moving beyond single-turn answer generation toward evolving clinical decision systems. Within an outpatient episode, they acquire evid

MeEvo: Metacognitive Evolution Combined with Natural Evolution for Automatic Heuristic Design

arXiv:2606.14202v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have advanced Automatic Heuristic Design (AHD) by enabling heuristic generation through reasoning and code synthe

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

model-releasesarxiv-cs-ai

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

Meshtryoshka: Differentiable Rendering of Real-World Scenes via Mesh Rasterization

arXiv:2606.28622v1 Announce Type: new Abstract: Differentiable rendering has emerged as a powerful approach for 3D reconstruction and novel view synthesis. State-of-the-art differentiable rendering me

applicationsarxiv-cs-cv

MIRROR: Aligning Semantic Relations from Language to Image via Gromov--Wasserstein

arXiv:2606.29462v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) inherit rich relational priors from their language backbones, yet often fail when asked to apply these relation

safetyarxiv-cs-cv

MirrorPPR: Exemplar-Based Portrait Photo Retouching

arXiv:2606.29308v1 Announce Type: new Abstract: While text-guided image editing has made remarkable progress, it remains limited in structural portrait retouching. Textual descriptions struggle to con

researcharxiv-cs-cv

Miti360: A Comprehensive Dataset for Improved Reforestation Monitoring

arXiv:2606.29447v1 Announce Type: new Abstract: Over the past decade, interest in applying machine learning (ML) to automate forest monitoring has grown significantly. However, existing training datas

researcharxiv-cs-cv

Mitigating Batch Effects in Histopathology via Language-Mediated Robust Embedding Generation

arXiv:2606.28697v1 Announce Type: cross Abstract: Pathology foundation models (PFMs) have demonstrated strong potential across clinical and scientific applications, yet their performance is often hind

researcharxiv-cs-cl

Mitigating the Safety-utility Trade-off in LLM Alignment via Adaptive Safe Context Learning

arXiv:2602.13562v2 Announce Type: replace-cross Abstract: While reasoning models have achieved remarkable success in complex reasoning tasks, their increasing power necessitates stringent safety measu

Model Directions, Not Words: Mechanistic Topic Models Using Sparse Autoencoders

arXiv:2507.23220v2 Announce Type: replace Abstract: Traditional topic models are effective at uncovering latent themes in large text collections. However, due to their reliance on bag-of-words represe

researcharxiv-cs-cl

Model Merging to Evolution: Parameter Space Exploration for Expert Models

model-releasesarxiv-cs-ai

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

Agents

Modeling Earth-Scale Human-Like Societies with One Billion Agents

arXiv:2506.12078v2 Announce Type: replace-cross Abstract: Understanding the dynamic evolution of complex social phenomena requires both high-fidelity modeling of human behavior and large-scale simulat

agentsarxiv-cs-ai

Modelling Human Values for Value-Aware Multi-Agent Systems

arXiv:2402.06359v2 Announce Type: replace Abstract: One of today's most pressing societal challenges is building AI systems whose behaviour, or the behaviour it enables within communities of interacti

MOSAIC: Orchestrating Collaborative Knowledge Tracing with Hierarchical Semantic Alignment

arXiv:2606.29049v1 Announce Type: new Abstract: Knowledge Tracing (KT) is important for personalized education but traditionally suffers from two key limitations: a reliance on shallow ID-based repres

safetyarxiv-cs-lg

MR-IQA: A Unified Margin View of Regression and Ranking for Blind Image Quality Assessment

arXiv:2606.29760v1 Announce Type: new Abstract: Blind image quality assessment (BIQA) is commonly built on two basic learning paradigms: regression and ranking. Regression calibrates absolute scores,

safetyarxiv-cs-cv

MSA-UNet3+: Multi-Scale Attention UNet3+ with New Supervised Prototypical Contrastive Loss for Coronary DSA Image Segmentation

arXiv:2504.05184v4 Announce Type: replace-cross Abstract: Accurate segmentation of coronary Digital Subtraction Angiography (DSA) images is essential for diagnosing and treating coronary artery diseas

Multi-Level Distributional Entropy for Explainable Network Intrusion Detection

arXiv:2606.29797v1 Announce Type: cross Abstract: Machine learning network intrusion detection systems (IDS) rely on aggregate flow statistics that discard distributional structure, while established

Multi-scale Object-Aware Gaze Estimation via Geometric Reasoning

arXiv:2606.29334v1 Announce Type: new Abstract: Gaze target estimation aims to predict the semantic object an observer fixates upon within an image, a task deeply rooted in the object-oriented nature

Multiply Robust Causal Mediation Analysis with Continuous Treatments

model-releasesarxiv-cs-lg

arXiv:2105.09254v4 Announce Type: replace-cross Abstract: In many applications, researchers are interested in the direct and indirect causal effects of a treatment or exposure on an outcome of interes

MuonSSM: Orthogonalizing State Space Models for Sequence Modeling

arXiv:2606.30461v1 Announce Type: new Abstract: State space models (SSMs) have emerged as efficient linear-time alternatives to attention for long-sequence modeling. However, existing SSMs often suffe

researcharxiv-cs-lg

Agents

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

agentsarxiv-cs-ai

Neuromorphic Energy-Aware Learning for Adaptive Deep Brain Stimulation

arXiv:2606.28600v1 Announce Type: cross Abstract: Neuromorphic and edge computing research has focused on reducing the inference cost of neural network controllers, yet in physical closed-loop systems

Tutorials

NIVA: A Multimodal Foundation Model for Actionable Earth System Intelligence

arXiv:2606.28546v1 Announce Type: new Abstract: Recent advances in AI-driven weather and climate modeling have improved forecast skill while reducing computational cost. However, existing data-driven

tutorialsarxiv-cs-lg

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

Nonlinear mixture model motivated subspace clustering

arXiv:2606.29261v1 Announce Type: cross Abstract: We derive the linear union-of-subspaces (UoS) model for subspace clustering (SC) from the nonlinear mixture model (NMM) used in blind source separatio

Not All Objectives Are Born Equal: Priority-Constrained Descent for Hierarchical Multi-Objective Optimization

arXiv:2606.29521v1 Announce Type: new Abstract: Deep learning problems rarely involve objectives that are equal in importance. A primary objective defines the goal, whilst secondary objectives, such a

researcharxiv-cs-lg

Offline Reinforcement Learning of High-Quality Behaviors Under Robust Style Alignment

arXiv:2601.22823v2 Announce Type: replace-cross Abstract: We study offline reinforcement learning of style-conditioned policies using explicit style supervision via subtrajectory labeling functions. I

Local Ai

One Forward Beats Two: InnerZoom for Accurate and Efficient GUI Grounding

arXiv:2606.30084v1 Announce Type: new Abstract: MLLM-based GUI grounding methods commonly formulate target localization as autoregressive coordinate generation, enabling models to leverage the strong

local-aiarxiv-cs-cv

Online Experiential Learning for Language Models

arXiv:2603.16856v2 Announce Type: replace Abstract: The prevailing paradigm for improving large language models relies on offline training with human annotations or simulated environments, leaving the

safetyarxiv-cs-cl

Tutorials

Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering

arXiv:2502.11491v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown remarkable capabilities in natural language processing. However, in knowledge graph question answering

tutorialsarxiv-cs-ai

OP3DSG: Open-Vocabulary Part-Aware 3D Scene Graph Generation for Real-World Environments

arXiv:2606.29786v1 Announce Type: new Abstract: 3D scene graphs (3DSGs) provide a compact and structured abstraction of 3D environments. Although advances in foundation models have enabled open-vocabu

OpenSPM: An Environment-Transferable Robotic Key Spatial Pose Memory and Closed-Loop High-Frequency Flow-Matching Action Generation Model

arXiv:2606.29936v1 Announce Type: new Abstract: Open-environment tabletop robotic manipulation requires systems to possess semantic understanding, precise geometric pose estimation, and high-frequency

researcharxiv-cs-ro

Optimization Dynamics Imprint Semantic Specificity in Contrastive Embedding Norms

arXiv:2606.30625v1 Announce Type: cross Abstract: Contrastive embedding models trained with scale-invariant losses are typically paired with distance metrics like cosine similarity, effectively ignori

Overcoming Dependent Censoring in the Evaluation of Survival Models

arXiv:2502.19460v4 Announce Type: replace-cross Abstract: Dependent censoring occurs when the event time and censoring time are not conditionally independent given the observed covariates. This compli

OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model

arXiv:2606.30421v1 Announce Type: new Abstract: Autonomous driving systems are steadily moving toward end-to-end paradigms to mitigate the limited adaptability of rule-based pipelines in complex traff

safetyarxiv-cs-cv

Parametric Skills

model-releasesarxiv-cs-cl

arXiv:2606.30015v1 Announce Type: new Abstract: Since intelligence fundamentally relies on efficient skill acquisition (Chollet, 2019), the ability to leverage skills is critical. For LLMs, skills, ma