Search: “evaluation”

Optimal differentially private kernel learning with random projection

arXiv:2507.17544v4 Announce Type: replace-cross Abstract: Differential privacy has become a cornerstone in the development of privacy-preserving learning algorithms. This work addresses optimizing dif

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OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction

DGX agent

arXiv:2604.25602v2 Announce Type: replace Abstract: Deploying production-ready multi-agent systems (MAS) in complex industrial environments remains challenging due to limitations in scalability, obser

agentsarxiv-cs-ai

30 Apr 2026

Parameterized Quantum Circuits as Feature Maps: Representation Quality and Readout Effects in Multispectral Land-Cover Classification

model-releasesarxiv-cs-lg

arXiv:2604.26675v1 Announce Type: cross Abstract: We investigate variational quantum classifiers (VQCs) for land-cover classification from multispectral satellite imagery, adopting a feature-map persp

Local Ai

Privacy-Preserving Federated Learning Framework for Distributed Chemical Process Optimization

arXiv:2604.26073v1 Announce Type: cross Abstract: Industrial chemical plants often operate under strict data confidentiality constraints, making centralized data-driven process modeling difficult. Fed

local-aiarxiv-cs-ai

Applications

Probabilistic data quality assessment for structural monitoring data via outlier-resistant conditional diffusion model

arXiv:2604.26366v1 Announce Type: cross Abstract: Data quality assessment is an essential step that ensures the reliability of the subsequent structural health monitoring (SHM) tasks. This study propo

applicationsarxiv-cs-lg

Probe-then-Plan: Environment-Aware Planning for Industrial E-commerce Search

arXiv:2603.15262v2 Announce Type: replace Abstract: Modern e-commerce search is evolving to resolve complex user intents. While Large Language Models (LLMs) offer strong reasoning, existing LLM-based

Tutorials

PromptEvolver: Prompt Inversion through Evolutionary Optimization in Natural-Language Space

arXiv:2604.06061v2 Announce Type: replace Abstract: Text-to-image generation has progressed rapidly, but faithfully generating complex scenes requires extensive trial-and-error to find the exact promp

tutorialsarxiv-cs-lg

q3-MuPa: Quick, Quiet, Quantitative Multi-Parametric MRI using Physics-Informed Diffusion Models

arXiv:2512.23726v2 Announce Type: replace-cross Abstract: The 3D fast silent multi-parametric mapping sequence with zero echo time (MuPa-ZTE) is a novel quantitative MRI (qMRI) acquisition that enable

Quantum Feature Selection with Higher-Order Binary Optimization on Trapped-Ion Hardware

model-releasesarxiv-cs-lg

arXiv:2604.26834v1 Announce Type: cross Abstract: We present a quantum feature-selection framework based on a higher-order unconstrained binary optimization (HUBO) formulation that explicitly incorpor

Quantum Gatekeeper: Multi-Factor Context-Bound Image Steganography with VQC Based Key Derivation on Quantum Hardware

arXiv:2604.26413v1 Announce Type: cross Abstract: This paper presents Quantum Gatekeeper, a context-bound image steganography framework where successful payload recovery depends on both cryptographic

QYOLO: Lightweight Object Detection via Quantum Inspired Shared Channel Mixing

model-releasesarxiv-cs-ai

arXiv:2604.26435v1 Announce Type: cross Abstract: The rapid advancement of object detection architectures has positioned single stage detectors as the dominant solution for real-time visual perception

RE-MCDF: Closed-Loop Multi-Expert LLM Reasoning for Knowledge-Grounded Clinical Diagnosis

arXiv:2602.01297v3 Announce Type: replace Abstract: Electronic medical records (EMRs), particularly in neurology, are inherently heterogeneous, sparse, and noisy, which poses significant challenges fo

agentsarxiv-cs-ai

Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies

arXiv:2604.26903v1 Announce Type: cross Abstract: This paper provides a concise yet comprehensive review of recent advancements in millimeter-wave (mm-wave) oscillators below 100 GHz and sub-terahertz

Recipes for Calibration Checks in Safety-Critical Applications

arXiv:2604.26479v1 Announce Type: cross Abstract: Safety-critical prediction systems, such as autonomous vehicles, weather forecasters, and medical monitors, commonly rely on probabilistic forecasters

safetyarxiv-cs-lg

Recurrence-Based Nonlinear Vocal Dynamics as Digital Biomarkers for Depression Detection from Conversational Speech

arXiv:2604.26242v1 Announce Type: cross Abstract: Digital biomarkers for depression have largely relied on static acoustic descriptors, pooled summary statistics, or conventional machine learning repr

Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding

arXiv:2604.26031v1 Announce Type: new Abstract: This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challen

researcharxiv-cs-cv

Resume-ing Control: (Mis)Perceptions of Agency Around GenAI Use in Recruiting Workflows

arXiv:2604.26851v1 Announce Type: cross Abstract: When generative AI (genAI) systems are used in high-stakes decision-making, its recommended role is to aid, rather than replace, human decision-making

Retrieval-Augmented LLMs for Evidence Localization in Clinical Trial Recruitment from Longitudinal EHR Narratives

model-releasesarxiv-cs-ai

arXiv:2604.05190v2 Announce Type: replace-cross Abstract: Screening patients for enrollment is a well-known, labor-intensive bottleneck that leads to under-enrollment and, ultimately, trial failures.

Rule-based High-Level Coaching for Goal-Conditioned Reinforcement Learning in Search-and-Rescue UAV Missions Under Limited-Simulation Training

arXiv:2604.26833v1 Announce Type: cross Abstract: This paper presents a hierarchical decision-making framework for unmanned aerial vehicle (UAV) missions motivated by search-and-rescue (SAR) scenarios

SAGE: A Strategy-Aware Graph-Enhanced Generation Framework For Online Counseling

arXiv:2604.26630v1 Announce Type: new Abstract: Effective mental health counseling is a complex, theory-driven process requiring the simultaneous integration of psychological frameworks, real-time dis

safetyarxiv-cs-cl

SciMDR: Advancing Scientific Multimodal Document Reasoning

model-releasesarxiv-cs-ai

arXiv:2603.12249v2 Announce Type: replace-cross Abstract: Constructing scientific multimodal document reasoning datasets for foundation model training involves an inherent trade-off among scale, faith

SEAL: Semantic-aware Single-image Sticker Personalization with a Large-scale Sticker-tag Dataset

model-releasesarxiv-cs-cv

arXiv:2604.26883v1 Announce Type: new Abstract: Synthesizing a target concept from a single reference image is challenging in diffusion-based personalized text-to-image generation, particularly for st

Local Ai

SecMate: Multi-Agent Adaptive Cybersecurity Troubleshooting with Tri-Context Personalization

arXiv:2604.26394v1 Announce Type: cross Abstract: Recent advances in large language models and agentic frameworks have enabled virtual customer assistants (VCAs) for complex support. We present SecMat

local-aiarxiv-cs-ai

Semi-supervised learning with max-margin graph cuts

arXiv:2604.26818v1 Announce Type: new Abstract: This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels

Similarity Choice and Negative Scaling in Supervised Contrastive Learning for Deepfake Audio Detection

arXiv:2604.26057v1 Announce Type: cross Abstract: Supervised contrastive learning (SupCon) is widely used to shape representations, but has seen limited targeted study for audio deepfake detection. Ex

SnapPose3D: Diffusion-Based Single-Frame 2D-to-3D Lifting of Human Poses

arXiv:2604.26620v1 Announce Type: new Abstract: Depth ambiguity and joint uncertainty are the two main obstacles in obtaining accurate human pose predictions by 2D-to-3D lifting methods proposed in th

researcharxiv-cs-cv

Sociodemographic Biases in Educational Counselling by Large Language Models

arXiv:2604.25932v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into educational settings, understanding their potential biases is critical. This study ex

Star-Fusion: A Multi-modal Transformer Architecture for Discrete Celestial Orientation via Spherical Topology

arXiv:2604.26582v1 Announce Type: cross Abstract: Reliable celestial attitude determination is a critical requirement for autonomous spacecraft navigation, yet traditional 'Lost-in-Space' (LIS) algori

agentsarxiv-cs-ai

Structured and Abstractive Reasoning on Multi-modal Relational Knowledge Images

arXiv:2510.21828v2 Announce Type: replace-cross Abstract: Understanding and reasoning with abstractive information from the visual modality presents significant challenges for current multi-modal larg

researcharxiv-cs-cl

SWAN: World-Aware Adaptive Multimodal Networks for Runtime Variations

arXiv:2604.26181v1 Announce Type: new Abstract: Multimodal deep neural networks deployed in realistic environments must contend with runtime variations: changes in modality quality, overall input comp

agentsarxiv-cs-lg

SynSur: An end-to-end generative pipeline for synthetic industrial surface defect generation and detection

arXiv:2604.26633v1 Announce Type: cross Abstract: The bottleneck in learning-based industrial defect detection is often limited not by model capacity, but by the scarcity of labeled defect data: defec

TAP into the Patch Tokens: Leveraging Vision Foundation Model Features for AI-Generated Image Detection

model-releasesarxiv-cs-cv

arXiv:2604.26772v1 Announce Type: new Abstract: Recent methods demonstrate that large-scale pretrained models, such as CLIP vision transformers, effectively detect AI-generated images (AIGIs) from uns

Tatemae: Detecting Alignment Faking via Tool Selection in LLMs

arXiv:2604.26511v1 Announce Type: cross Abstract: Alignment faking (AF) occurs when an LLM strategically complies with training objectives to avoid value modification, reverting to prior preferences o

Teaching LLM to be Persuasive: Reward-Enhanced Policy Optimization for Alignment from Heterogeneous Rewards

arXiv:2510.04214v3 Announce Type: replace Abstract: We deploy large language models (LLMs) as business development (BD) agents for persuasive price negotiation in online travel agencies (OTAs). The ag

safetyarxiv-cs-cl

The Bandit's Blind Spot: The Critical Role of User State Representation in Recommender Systems

arXiv:2604.26651v1 Announce Type: cross Abstract: With the increasing availability of online information, recommender systems have become an important tool for many web-based systems. Due to the conti

Industry

The @huggingface CLI now includes a command to find the best open-source models for a given dataset! This is going to be very useful for age…

Hugging Face introduced a new CLI command that helps users identify the best open-source models suited for their specific datasets, streamlining the model selection process. This feature reduces the m

industryclem-delangue--x

Three-Step Nav: A Hierarchical Global-Local Planner for Zero-Shot Vision-and-Language Navigation

arXiv:2604.26946v1 Announce Type: new Abstract: Breakthrough progress in vision-based navigation through unknown environments has been achieved by using multimodal large language models (MLLMs). These

agentsarxiv-cs-cv

Today we’re releasing Qwen-Scope 🔭, an open suite of sparse autoencoders for the Qwen model family. It turns SAE features into practical to…

Today we’re releasing Qwen-Scope 🔭, an open suite of sparse autoencoders for the Qwen model family. It turns SAE features into practical tools： 🎯 Inference — Steer model outputs by directly manipulati

model-releasesqwen--x

Translating Under Pressure: Domain-Aware LLMs for Crisis Communication

arXiv:2604.26597v1 Announce Type: cross Abstract: Timely and reliable multilingual communication is critical during natural and human-induced disasters, but developing effective solutions for crisis c

Applications

Tree-of-Evidence: Efficient 'System 2' Search for Faithful Multimodal Grounding

arXiv:2604.07692v2 Announce Type: replace Abstract: Large Multimodal Models (LMMs) achieve state-of-the-art performance in high-stakes domains like healthcare, yet their reasoning remains opaque. Curr

applicationsarxiv-cs-lg

Uncertainty-Aware Information Pursuit for Interpretable and Reliable Medical Image Analysis

arXiv:2506.16742v3 Announce Type: replace Abstract: To be adopted in safety-critical domains like medical image analysis, AI systems must provide human-interpretable decisions. Variational Information

safetyarxiv-cs-cv

Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics

arXiv:2604.26836v1 Announce Type: new Abstract: Predictive safety filters (PSFs) leverage model predictive control to enforce constraint satisfaction during deep reinforcement learning (RL) exploratio

safetyarxiv-cs-lg

Understanding DNNs in Feature Interaction Models: A Dimensional Collapse Perspective

arXiv:2604.26489v1 Announce Type: new Abstract: DNNs have gained widespread adoption in feature interaction recommendation models. However, there has been a longstanding debate on their roles. On one

Unifying Runtime Monitoring Approaches for Safety-Critical Machine Learning: Application to Vision-Based Landing

arXiv:2604.26411v1 Announce Type: new Abstract: Runtime monitoring is essential to ensure the safety of ML applications in safety-critical domains. However, current research is fragmented, with indepe

safetyarxiv-cs-lg

Vibe Check: Understanding the Effects of LLM-Based Conversational Agents' Personality and Alignment on User Perceptions in Goal-Oriented Tasks

arXiv:2509.09870v2 Announce Type: replace-cross Abstract: Large language models (LLMs) enable conversational agents (CAs) to express distinctive personalities, raising new questions about how such des

Applications

Virtual-reality based patient-specific simulation of spine surgical procedures: A fast, highly automated and high-fidelity system for surgical education and planning

arXiv:2604.26781v1 Announce Type: new Abstract: Surgical training involves didactic teaching, mentor-led learning, surgical skills laboratories, and direct exposure to surgery; however, increasing cli

applicationsarxiv-cs-cv

What Google Cloud announced in AI this month

model-releasesgoogle-cloud-ai

Editor’s note: Want to keep up with the latest from Google Cloud? Check back here for a monthly recap of our latest updates, announcements, resources, events, learning opportunities, and more. We host

When Hidden States Drift: Can KV Caches Rescue Long-Range Speculative Decoding?

arXiv:2604.26412v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference, but SOTA hidden-state-based drafters suffer from long-range decay: draft accuracy degrades as the specul

researcharxiv-cs-cl