Search: “framework”

Unified Multi-Foundation-Model Slide Representation for Pan-Cancer Recognition and Text-Guided Tumor Localization

arXiv:2604.22846v1 Announce Type: new Abstract: The expanding ecosystem of pathology foundation models has produced powerful but fragmented tile-level representations, limiting their use in clinical t

local-aiarxiv-cs-cv

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Safety

UNSEEN: A Cross-Stack LLM Unlearning Defense against AR-LLM Social Engineering Attacks

DGX agent

arXiv:2604.23141v1 Announce Type: cross Abstract: Emerging AR-LLM-based Social Engineering attack (e.g., SEAR) is at the edge of posing great threats to real-world social life. In such AR-LLM-SE attac

safetyarxiv-cs-ai

28 Apr 2026

Usable Agent Discovery for Decentralized AI Systems

arXiv:2604.23080v1 Announce Type: cross Abstract: Large-scale agentic systems run on distributed infrastructures where many software agents share physical hosts and are discovered via peer-to-peer mec

agentsarxiv-cs-ai

Utility-Aware Data Pricing: Token-Level Quality and Empirical Training Gain for LLMs

arXiv:2604.22893v1 Announce Type: cross Abstract: Traditional data valuation methods based on ``row-count imes quality coefficient'' paradigms fail to capture the nuanced, nonlinear contributions that

Variational Grey-Box Dynamics Matching

arXiv:2602.17477v3 Announce Type: replace Abstract: Deep generative models such as flow matching and diffusion models have shown great potential in learning complex distributions and dynamical systems

applicationsarxiv-cs-lg

VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translation

arXiv:2604.22942v1 Announce Type: cross Abstract: Diffusion models produce high-quality synthetic data but suffer from slow inference. We propose 3D Variable-Step Denoising Diffusion Probabilistic Mod

Why Architecture Choice Matters in Symbolic Regression

arXiv:2604.23256v1 Announce Type: cross Abstract: Symbolic regression discovers mathematical formulas from data. Some methods fix a tree of operators, assign learnable weights, and train by gradient d

WildLIFT: Lifting monocular drone video to 3D for species-agnostic wildlife monitoring

arXiv:2604.24718v1 Announce Type: new Abstract: Monocular RGB cameras mounted on drones are widely used for wildlife monitoring, yet most analytical pipelines remain confined to two-dimensional image

researcharxiv-cs-cv

ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems

arXiv:2604.23878v1 Announce Type: new Abstract: Despite a century of empirical memory research, existing AI agent memory systems rely on system-engineering metaphors (virtual-memory paging, flat LLM s

Tutorials

ZID-Net: Zero-Inference Diffusion Prior Decoupling Network for Single Image Dehazing

arXiv:2604.23709v1 Announce Type: new Abstract: Single image dehazing is often constrained by a trade-off between restoration quality and computational efficiency. While efficient, CNN networks strugg

tutorialsarxiv-cs-cv

A Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex Societies

arXiv:2604.22227v1 Announce Type: cross Abstract: Classical robot ethics is often framed around obedience, most famously through Asimov's laws. This framing is too narrow for contemporary AI systems,

Adversarial Malware Generation in Linux ELF Binaries via Semantic-Preserving Transformations

arXiv:2604.22639v1 Announce Type: cross Abstract: Malware development and detection have undergone significant changes in recent years as modern concepts, such as machine learning, have been used for

AgentSearchBench: A Benchmark for AI Agent Search in the Wild

model-releasesarxiv-cs-ai

arXiv:2604.22436v1 Announce Type: new Abstract: The rapid growth of AI agent ecosystems is transforming how complex tasks are delegated and executed, creating a new challenge of identifying suitable a

Algorithmic Compliance and Regulatory Loss in Digital Assets

arXiv:2603.04328v2 Announce Type: replace Abstract: We study the deployment performance of machine learning based enforcement systems used in cryptocurrency anti money laundering (AML). Using forward

applicationsarxiv-cs-lg

ArmSSL: Adversarial Robust Black-Box Watermarking for Self-Supervised Learning Pre-trained Encoders

model-releasesarxiv-cs-ai

arXiv:2604.22550v1 Announce Type: cross Abstract: Self-supervised learning (SSL) encoders are invaluable intellectual property (IP). However, no existing SSL watermarking for IP protection can concurr

Asymmetric Goal Drift in Coding Agents Under Value Conflict

model-releasesarxiv-cs-ai

arXiv:2603.03456v2 Announce Type: replace Abstract: Coding agents are increasingly deployed autonomously, at scale, and over long-context horizons. To be effective and safe, these agents must navigate

ATRS: Adaptive Trajectory Re-splitting via a Shared Neural Policy for Parallel Optimization

model-releasesarxiv-cs-ro

arXiv:2604.22715v1 Announce Type: new Abstract: Parallel trajectory optimization via the Alternating Direction Method of Multipliers (ADMM) has emerged as a scalable approach to long-horizon motion pl

CGC: Compositional Grounded Contrast for Fine-Grained Multi-Image Understanding

arXiv:2604.22498v1 Announce Type: cross Abstract: Although Multimodal Large Language Models (MLLMs) have advanced rapidly, they still face notable challenges in fine-grained multi-image understanding,

CharTide: Data-Centric Chart-to-Code Generation via Tri-Perspective Tuning and Inquiry-Driven Evolution

model-releasesarxiv-cs-cv

arXiv:2604.22192v1 Announce Type: new Abstract: Chart-to-code generation demands strict visual precision and syntactic correctness from Vision-Language Models (VLMs). However, existing approaches are

CodeGraphVLP: Code-as-Planner Meets Semantic-Graph State for Non-Markovian Vision-Language-Action Models

arXiv:2604.22238v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models promise generalist robot manipulation, but are typically trained and deployed as short-horizon policies that assume

applicationsarxiv-cs-ro

CognitiveTwin: Robust Multi-Modal Digital Twins for Predicting Cognitive Decline in Alzheimer's Disease

arXiv:2604.22428v1 Announce Type: new Abstract: Predicting individual cognitive decline in Alzheimer's disease (AD) is difficult due to the heterogeneity of disease progression. Reliable clinical tool

Conformalized Super Learner

arXiv:2604.22391v1 Announce Type: cross Abstract: The Super Learner (SL) is a widely used ensemble method that combines predictions from a library of learners based on their predictive performance. In

Contrastive Semantic Projection: Faithful Neuron Labeling with Contrastive Examples

arXiv:2604.22477v1 Announce Type: new Abstract: Neuron labeling assigns textual descriptions to internal units of deep networks. Existing approaches typically rely on highly activating examples, often

applicationsarxiv-cs-cv

Cross-Domain Offshore Wind Power Forecasting: Transfer Learning Through Meteorological Clusters

arXiv:2601.19674v2 Announce Type: replace-cross Abstract: Ambitious decarbonisation targets are rapidly increasing the commission of new offshore wind farms. For these newly commissioned plants to run

da4ml: Distributed Arithmetic for Real-time Neural Networks on FPGAs

arXiv:2507.04535v2 Announce Type: replace-cross Abstract: Neural networks with a latency requirement on the order of microseconds, like the ones used at the CERN Large Hadron Collider, are typically d

Decoding High-Dimensional Finger Motion from EMG Using Riemannian Features and RNNs

model-releasesarxiv-cs-lg

arXiv:2604.22499v1 Announce Type: new Abstract: Continuous estimation of high-dimensional finger kinematics from forearm surface electromyography (EMG) could enable natural control for hand prostheses

Depth-Aware Rover: A Study of Edge AI and Monocular Vision for Real-World Implementation

arXiv:2604.22331v1 Announce Type: new Abstract: This study analyses simulated and real-world implementations of depth-aware rover navigation, highlighting the transition from stereo vision to monocula

local-aiarxiv-cs-cv

DM^3-Nav: Decentralized Multi-Agent Multimodal Multi-Object Semantic Navigation

arXiv:2604.22014v1 Announce Type: cross Abstract: We present DM^3-Nav, a fully decentralized multi-agent semantic navigation system supporting multimodal open-vocabulary goal specification and multi-o

agentsarxiv-cs-ro

DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale

arXiv:2604.00813v3 Announce Type: replace-cross Abstract: End-to-end autonomous driving has evolved from the conventional paradigm based on sparse perception into vision-language-action (VLA) models,

agentsarxiv-cs-ai

Dynamically Acquiring Text Content to Enable the Classification of Lesser-known Entities for Real-world Tasks

arXiv:2604.22325v1 Announce Type: new Abstract: Existing Natural Language Processing (NLP) resources often lack the task-specific information required for real-world problems and provide limited cover

applicationsarxiv-cs-cl

Efficient Diffusion Distillation via Embedding Loss

arXiv:2604.22379v1 Announce Type: new Abstract: Recent advances in distilling expensive diffusion models into efficient few-step generators show significant promise. However, these methods typically d

researcharxiv-cs-cv

Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search

arXiv:2502.00955v2 Announce Type: replace Abstract: Monte Carlo Tree Search (MCTS) based methods provide promising approaches for generating synthetic data to enhance the self-training of Large Langua

agentsarxiv-cs-cl

FeatEHR-LLM: Leveraging Large Language Models for Feature Engineering in Electronic Health Records

arXiv:2604.22534v1 Announce Type: cross Abstract: Feature engineering for Electronic Health Records (EHR) is complicated by irregular observation intervals, variable measurement frequencies, and struc

applicationsarxiv-cs-ai

FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision

model-releasesarxiv-cs-cv

arXiv:2604.22093v1 Announce Type: new Abstract: Reliable visual perception under low illumination remains a core challenge for autonomous robotic systems, where degraded image quality directly comprom

FMSD-TTS: Few-shot Multi-Speaker Multi-Dialect Text-to-Speech Synthesis for U-Tsang, Amdo and Kham Speech Dataset Generation

arXiv:2505.14351v4 Announce Type: replace-cross Abstract: Tibetan is a low-resource language with minimal parallel speech corpora spanning its three major dialects-U-Tsang, Amdo, and Kham-limiting pro

GazeVLA: Learning Human Intention for Robotic Manipulation

arXiv:2604.22615v1 Announce Type: new Abstract: Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstra

applicationsarxiv-cs-ro

GenMatter: Perceiving Physical Objects with Generative Matter Models

arXiv:2604.22160v1 Announce Type: cross Abstract: Human visual perception offers valuable insights for understanding computational principles of motion-based scene interpretation. Humans robustly dete

local-aiarxiv-cs-ai

HACHIMI: Scalable and Controllable Student Persona Generation via Orchestrated Agents

arXiv:2603.04855v3 Announce Type: replace Abstract: Student Personas (SPs) are emerging as infrastructure for educational LLMs, yet prior work often relies on ad-hoc prompting or hand-crafted profiles

agentsarxiv-cs-cl

How Many Visual Levers Drive Urban Perception? Interventional Counterfactuals via Multiple Localised Edits

arXiv:2604.22103v1 Announce Type: cross Abstract: Street-view perception models predict subjective attributes such as safety at scale, but remain correlational: they do not identify which localized vi

safetyarxiv-cs-cv

How Supply Chain Dependencies Complicate Bias Measurement and Accountability Attribution in AI Hiring Applications

arXiv:2604.22679v1 Announce Type: cross Abstract: The increasing adoption of AI systems in hiring has raised concerns about algorithmic bias and accountability, prompting regulatory responses includin

local-aiarxiv-cs-ai

Introducing Background Temperature to Characterise Hidden Randomness in Large Language Models

arXiv:2604.22411v1 Announce Type: new Abstract: Even when decoding with temperature T=0, large language models (LLMs) can produce divergent outputs for identical inputs. Recent work by Thinking Machin

Learning-augmented robotic automation for real-world manufacturing

arXiv:2604.22235v1 Announce Type: cross Abstract: Industrial robots are widely used in manufacturing, yet most manipulation still depends on fixed waypoint scripts that are brittle to environmental ch

Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching

arXiv:2604.22061v1 Announce Type: cross Abstract: Patient-trial matching requires reasoning over long, heterogeneous electronic health records (EHRs) and complex eligibility criteria, posing significa

applicationsarxiv-cs-ai

Logistic Bandits with ilde{O}(sqrt{dT}) Regret without Context Diversity Assumptions

arXiv:2604.22161v1 Announce Type: new Abstract: We study the K-armed logistic bandit problem, where at each round, the agent observes K feature vectors associated with K actions. Existing approaches t

agentsarxiv-cs-lg

Mochi: Aligning Pre-training and Inference for Efficient Graph Foundation Models via Meta-Learning

arXiv:2604.22031v1 Announce Type: cross Abstract: We propose Mochi, a Graph Foundation Model that addresses task unification and training efficiency by adopting a meta-learning based training framewor

applicationsarxiv-cs-ai

Near-Optimal Regret for the Safe Learning-based Control of the Constrained Linear Quadratic Regulator

arXiv:2604.22158v1 Announce Type: cross Abstract: We study the problem of adaptive control of the stochastic linear quadratic regulator (LQR) with constraints that must be satisfied at every time step

safetyarxiv-cs-lg

Null-Space Flow Matching for MIMO Channel Estimation in Latency-Constrained Systems

arXiv:2604.22005v1 Announce Type: cross Abstract: Accurate yet low-latency channel state information (CSI) acquisition is essential for multiple-input multiple-output (MIMO) communication systems. Whi

OREN: Octree Residual Network for Real-Time Euclidean Signed Distance Mapping

arXiv:2510.18999v2 Announce Type: replace-cross Abstract: Reconstructing signed distance functions (SDFs) from point cloud data benefits many robot autonomy capabilities, including localization, mappi