Search: “evaluation”

OGD4All: A Framework for Accessible Interaction with Geospatial Open Government Data Based on Large Language Models

arXiv:2602.00012v3 Announce Type: replace Abstract: We present OGD4All, a transparent, auditable, and reproducible framework based on Large Language Models (LLMs) to enhance citizens' interaction with

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One-Shot Data Selection for Medical Image Classification via Graph Coverage

DGX agent

arXiv:2606.22002v1 Announce Type: new Abstract: Training medical image classifiers on entire datasets is wasteful when annotation budgets are limited: not all samples contribute equally, yet acquiring

local-aiarxiv-cs-cv

23 Jun 2026

Oracle-RLAIF: An Improved Fine-Tuning Framework for Multi-modal Video Models using Reinforcement Learning from Ranking Feedback

arXiv:2510.02561v2 Announce Type: replace Abstract: Recent advances in large video-language models (VLMs) rely on extensive fine-tuning techniques that strengthen alignment between textual and visual

ORBIT: Training-Free Multi-Attribute Behavioral Steering via Orthogonal Subspace Rotation

arXiv:2606.22357v1 Announce Type: cross Abstract: Language models are widely used in assistant settings, where controlling behavioral attributes is often essential. Activation steering modifies hidden

Local Ai

P-JEPA: Procedural Video Representation Learning via Joint Embedding Predictive Architecture

arXiv:2606.23256v1 Announce Type: new Abstract: The increasing maturity of embodied AI platforms has driven a growing interest in procedural video representation learning to support intelligent assist

local-aiarxiv-cs-cv

PEAR: Permutation-Equivariant Adaptive Routing Multi-Agent Debate

arXiv:2606.20621v1 Announce Type: cross Abstract: Multi-agent debate improves the reliability of large language models (LLMs) through iterative peer critiques. However, fixed topologies often introduc

agentsarxiv-cs-lg

PenduMorph: Development and Motion Analysis of Pendulum-Actuated Rolling Reconfigurable Spherical Robot with Magnetic-Coupling

arXiv:2606.22491v1 Announce Type: new Abstract: This paper presents 'PenduMorph', a wireless reconfigurable rolling spherical robot designed as a modular platform for enclosed locomotion and inter-mod

researcharxiv-cs-ro

PG-MAP: Joint MAP Optimization for Inference-Time Alignment of Diffusion and Flow-Matching Models

arXiv:2606.22958v1 Announce Type: cross Abstract: Inference-time alignment of pretrained text-to-image models is typically performed along a single control axis, such as classifier-free guidance, atte

phi-Scene: Physically Grounded Image-to-3D Scene Reconstruction

arXiv:2606.21596v1 Announce Type: new Abstract: Reconstructing compositional 3D scenes from a single image is a fundamental challenge in 3D world modeling. Recent methods can recover high-fidelity, co

PHOEBI: An Open-World Benchmark for Bacterial Identification in Phase-Contrast Microscopy

arXiv:2606.22890v1 Announce Type: new Abstract: Optical microscopy enables rapid, label-free imaging of live bacteria and is the standard instrument for species identification across clinical, environ

Physically-guided Image Generation for Multi-Projection Mapping

arXiv:2606.22477v1 Announce Type: new Abstract: Projection Mapping (PM) enables seamless superimposition of digital content onto real-world 3D objects, serving as a fundamental technique for immersive

PIAvatar: Physically Interactive Avatars via Deformation Gradient Decoupling

arXiv:2606.21162v1 Announce Type: cross Abstract: 3D human avatars have shown impressive visual fidelity driven by pose-conditioned models, yet they still lack the physical ability required for intera

Polynomial Dice Loss for Medical Image Segmentation

arXiv:2606.23373v1 Announce Type: new Abstract: Medical image segmentation is a fundamental task for medical image processing and computer-assisted intervention, yet data imbalance and small lesion de

Precision Recall Controllable Radiology Report Generation via Hybrid Natural Language and Clinical Reward Learning

arXiv:2606.21447v1 Announce Type: cross Abstract: Automated radiology report generation (RRG) has gained increasing attention because it can reduce the heavy workload of clinical report writing. Howev

Predictive Feature Caching for Training-free Acceleration of Molecular Geometry Generation

arXiv:2510.04646v2 Announce Type: replace Abstract: Flow matching models generate high-fidelity molecular geometries but incur significant computational costs during inference, requiring hundreds of n

Priority-Aware Learning-Unlearning Correction for Dynamic Decentralized LoRA Fine-Tuning

arXiv:2606.22878v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed at the network edge to provide pervasive generative AI services, decentralized federated learn

Privacy-Preserving Federated Temporal Graph Learning with Digital Twin--Guided Adaptive Deception for Cyber-Resilient IoMT

arXiv:2606.21513v1 Announce Type: new Abstract: The rapid proliferation of IoT and IoMT devices introduces critical cybersecurity vulnerabilities in healthcare and industrial environments where resour

agentsarxiv-cs-lg

Privacy-Preserving Person Re-Identification from Temporal Sequences with Transformer and Hungarian Optimization

arXiv:2606.23230v1 Announce Type: new Abstract: Person re-identification (Re-ID) is a crucial task in surveillance and human behavior analysis, often used in public spaces such as transport hubs. Trad

Probe-and-Refine Tuning of Repository Guidance for Coding Agents

arXiv:2606.20512v2 Announce Type: replace-cross Abstract: LLM-based coding agents need higher-level operational knowledge about a repository (which files house which subsystems, how to run the test su

PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs

arXiv:2606.22914v1 Announce Type: new Abstract: Activities in numerous evolving systems can be represented as dynamic graphs in snapshot form at different time intervals, i.e., discrete-time dynamic g

Prompting Diffusion Models for Zero-Shot Instance Segmentation

arXiv:2606.22660v1 Announce Type: new Abstract: Several disruptive research directions have recently emerged in computer vision, including foundation models achieving previously unseen zero-shot perfo

Protein contacts are already in the attention: a single-forward-pass alternative to the Categorical Jacobian

arXiv:2606.21876v1 Announce Type: new Abstract: The Categorical Jacobian (CJ) of Zhang et al. (2024) reads protein contacts from a language model by perturbing every residue with every alternative ami

QeHDC: Hyperdimensional Computing based on Quantum-enhanced binding and SuperClass Construction

arXiv:2606.22421v1 Announce Type: new Abstract: Hyperdimensional Computing (HDC) is a robust computational framework inspired by human cognition characterized by simple and efficient operations within

Quantile Adaptive Temperature Scaling for Confidence Calibration

arXiv:2606.21749v1 Announce Type: new Abstract: Deep neural networks often produce poorly calibrated confidence estimates, overstating their certainty even when predictions are incorrect. Temperature

QuantKAN: A Unified Quantization Framework for Kolmogorov Arnold Networks

arXiv:2511.18689v4 Announce Type: replace Abstract: Kolmogorov--Arnold Networks (KANs) replace linear weights with spline-based functions, offering strong expressivity but posing challenges for low-pr

Quantum Convolutional Neural Networks for Groundwater Heat Plume Prediction: A Surrogate Modeling Approach

arXiv:2606.23411v1 Announce Type: cross Abstract: Quantum machine learning methods are increasingly explored for modeling complex environmental systems, including groundwater heat plume dynamics. In t

RAPID: A Reproducible Multi-Agent Pipeline for Interpretable Disaster Damage Assessment from Satellite and Street-View Imagery

arXiv:2606.21819v1 Announce Type: new Abstract: Due to the increasing frequency and intensity of extreme climate events, there is a clear demand for intelligent, scalable, and autonomous approaches to

agentsarxiv-cs-cv

Real-World Deployment of Massively Parallel Sampling-Based MPC for Contact-Rich Manipulation

arXiv:2606.20712v1 Announce Type: new Abstract: Sampling-based Model Predictive Control (SMPC) is a promising strategy for contact-rich robotic manipulation, combining gradient-free optimization with

hardwarearxiv-cs-ro

Real5-OmniDocBench: A Full-Scale Physical Reconstruction Benchmark for Robust Document Parsing in the Wild

arXiv:2603.04205v2 Announce Type: replace Abstract: While Vision-Language Models (VLMs) achieve near-perfect scores on digital document benchmarks like OmniDocBench, their performance in the unpredict

RECALL: Recovery Experience Collection for Active Lifelong Learning in Vision-Language-Action Models

arXiv:2606.23617v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are commonly fine-tuned through passive imitation learning, where additional demonstrations are collected for task

safetyarxiv-cs-lg

Recency/Frequency Adaptive KV Caching for Large Language Model Serving

arXiv:2606.21238v1 Announce Type: cross Abstract: Key-value (KV) caching is a powerful technique for accelerating large language model inference and generation. Inference workloads are large and diver

safetyarxiv-cs-lg

ReconMIL: Synergizing Latent Space Reconstruction with Bi-Stream Mamba for Whole Slide Image Analysis

arXiv:2603.19925v2 Announce Type: replace-cross Abstract: Whole slide image (WSI) analysis heavily relies on multiple instance learning (MIL). While recent methods benefit from large-scale foundation

Region-Specific Calibration Achieves Excellent Inter-Device Reliability for Smartphone Dermatology: A Multi-Device Benchmark on Korean Facial Skin

arXiv:2512.21988v3 Announce Type: replace-cross Abstract: Background: Smartphone-based dermatology requires inter-device colorimetric reliability that holds across calibration regimes, yet quantitativ

Reinforcement Learning-Based Traffic Signal Control for IoT-Enabled Intersections

arXiv:2606.22108v1 Announce Type: cross Abstract: Urban traffic congestion remains a persistent challenge in car-dependent cities, imposing significant economic and societal costs. Traffic signal syst

safetyarxiv-cs-lg

Reinforcement learning to improve large language model-based automated code compliance systems

arXiv:2606.22402v1 Announce Type: cross Abstract: Large language model (LLM)-based approaches for automated code compliance (ACC) of building regulations are prone to generating incorrect and hallucin

Reliability-Guided Adaptive Ensembling for Robust Test-Time Adaptation

arXiv:2606.22351v1 Announce Type: cross Abstract: Test-time adaptation (TTA) can mitigate domain shift without source data, but it is highly brittle under adversarially contaminated test streams, wher

Remember what you did?: Learning Behavioral Memories for Partially Observable Object Manipulation

arXiv:2606.21188v1 Announce Type: new Abstract: Long horizon, contact-rich manipulation is inherently partially observable. This is as a single visual observation rarely captures a robot's full action

safetyarxiv-cs-ro

Residue-Level Attributions in Protein Language Models Do Not Recover Allergen Epitopes

arXiv:2606.22181v1 Announce Type: new Abstract: Deep allergenicity classifiers are increasingly used in safety screening of novel foods, and recent protein language models have substantially improved

Retrieval-Augmented Anatomical Guidance for Text-to-CT Generation

arXiv:2603.08305v2 Announce Type: replace Abstract: Text-conditioned generative models for volumetric medical imaging provide semantic control but lack explicit anatomical guidance, often resulting in

Reward-free Pretraining for Reinforcement Learning via Occupancy Coverage Maximization

arXiv:2606.21271v1 Announce Type: new Abstract: Sparse rewards pose a central challenge in reinforcement learning, since agents receive no informative signal until they reach their goal. Intrinsic-rew

Right Knowledge, Wrong Answer: Test-Time Steering for Temporal Fact Conflicts in Open-Weight Language Models

arXiv:2606.20959v1 Announce Type: new Abstract: Large language models can store both outdated facts and newer superseding facts in their parameters, but standard prompting may still elicit the outdate

Robot Self-Improvement via Human-Video Dynamics Models

arXiv:2606.21406v1 Announce Type: cross Abstract: A central question in robot learning is how to acquire skills from the kinds of data that humans learn from: passive observation, embodied practice, a

Robust and Differentially Private Principal Component Analysis

arXiv:2507.15232v2 Announce Type: replace-cross Abstract: Recent advances have sparked significant interest in the development of privacy-preserving Principal Component Analysis (PCA). However, many e

RocketPFN: Accurate Time Series Classification via In-Context Learning

arXiv:2606.21786v1 Announce Type: new Abstract: We introduce RocketPFN, a training-free pipeline for time series classification that combines random convolutional feature extraction (Rocket) with in-c

RogueRover: Autonomous Rogue Device Localization for Incident Response

arXiv:2606.21264v1 Announce Type: new Abstract: Physically localizing unauthorized wireless devices remains a critical bottleneck in cyber-physical security operations, where rogue access points can p

agentsarxiv-cs-ro

RubricRL: Simple Generalizable Rewards for Text-to-Image Generation

arXiv:2511.20651v2 Announce Type: replace Abstract: Reinforcement learning (RL) has recently emerged as a promising approach for aligning text-to-image generative models with human preferences. A key

SAGE: An Expert-Annotated South Asian GI Endoscopy Dataset for Multimodal Learning and Hallucination Analysis

arXiv:2606.22144v1 Announce Type: new Abstract: Gastrointestinal cancers represent a growing health burden in the South Asian region, driven largely by rapid changes in socio-economic conditions & lif