Search: “evaluation”

CineMesh4D: Personalized 4D Whole Heart Reconstruction from Sparse Cine MRI

arXiv:2605.13994v1 Announce Type: cross Abstract: Accurate 3D+t whole-heart mesh reconstruction from cine MRI is a clinically crucial yet technically challenging task. The difficulty of this task aris

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CoCoEdit: Content-Consistent Image Editing via Region Regularized Reinforcement Learning

DGX agent

arXiv:2602.14068v2 Announce Type: replace Abstract: Image editing has achieved impressive results with the development of large-scale generative models. However, existing models mainly focus on the ed

model-releasesarxiv-cs-cv

15 May 2026

Collaborative Yet Personalized Policy Training: Single-Timescale Federated Actor-Critic

arXiv:2605.14423v1 Announce Type: cross Abstract: Despite the popularity of the actor-critic method and the practical needs of collaborative policy training, existing works typically either overlook e

safetyarxiv-cs-ai

Communication-Efficient Federated Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2505.04535v3 Announce Type: replace Abstract: Federated Learning (FL) enables the utilization of vast, previously inaccessible data sources. At the same time, pre-trained Language Models (LMs) h

Local Ai

ContextFlow: Context-Aware Flow Matching For Trajectory Inference From Spatial Omics Data

arXiv:2510.02952v3 Announce Type: replace Abstract: Inferring trajectories from longitudinal spatially-resolved omics data is fundamental to understanding the dynamics of structural and functional tis

local-aiarxiv-cs-lg

CoralLite: {mu}CT Reconstruction of Coral Colonies from Individual Corallites

arXiv:2605.15093v1 Announce Type: new Abstract: The life history of an individual coral is archived within the accreting skeleton of the colony. While reef-forming coral colonies (e.g. massive Porites

researcharxiv-cs-cv

COREKG: Coreset-Guided Personalized Summarization of Knowledge Graphs

arXiv:2605.14900v1 Announce Type: new Abstract: Knowledge Graphs (KGs) are extensively used across different domains and in several applications. Often, these KGs are very large in size. Such KGs beco

Agents

COTCAgent: Preventive Consultation via Probabilistic Chain-of-Thought Completion

arXiv:2605.15016v1 Announce Type: cross Abstract: As large language models empower healthcare, intelligent clinical decision support has developed rapidly. Longitudinal electronic health records (EHR)

agentsarxiv-cs-ai

Covariance-aware sampling for Diffusion Models

arXiv:2605.13910v1 Announce Type: cross Abstract: We present a covariance-aware sampler that improves the quality of pixel-space Diffusion Model (DM) sampling in the few-step regime. We hypothesize th

researcharxiv-cs-cv

CreFlow: Corrective Reflow for Sparse-Reward Embodied Video Diffusion RL

arXiv:2605.14274v1 Announce Type: new Abstract: Video generation models trained on heterogeneous data with likelihood-surrogate objectives can produce visually plausible rollouts that violate physical

researcharxiv-cs-cv

Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets

arXiv:2605.15079v1 Announce Type: new Abstract: Croissant has emerged as the metadata standard for machine learning datasets, providing a structured, JSON-LD-based format that makes dataset discovery,

researcharxiv-cs-lg

Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement

arXiv:2605.14759v1 Announce Type: new Abstract: De novo crystal generation seeks to discover materials that are not merely realistic, but also stable and novel. However, most existing generative model

researcharxiv-cs-lg

CSI-JEPA: Towards Foundation Representations for Ubiquitous Sensing with Minimal Supervision

arXiv:2605.14171v1 Announce Type: new Abstract: Channel state information (CSI) provides a widely available sensing modality for human and environment perception, but existing CSI sensing models usual

applicationsarxiv-cs-lg

CUICurate: A GraphRAG-based Framework for Automated Clinical Concept Curation for NLP applications

arXiv:2602.17949v2 Announce Type: replace-cross Abstract: Background: Clinical named entity recognition tools commonly map free text to Unified Medical Language System (UMLS) Concept Unique Identifier

Darwin Family: MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling of Language-Model Reasoning

arXiv:2605.14386v1 Announce Type: cross Abstract: We present Darwin Family, a framework for training-free evolutionary merging of large language models via gradient-free weight-space recombination. We

Decoupling Stability and Plasticity for Multi-Modal Test-Time Adaptation

arXiv:2603.00574v2 Announce Type: replace-cross Abstract: Adapting pretrained multi-modal models to evolving test-time distributions, known as multi-modal test-time adaptation, presents a significant

Deep Image Segmentation via Discriminant Feature Learning

model-releasesarxiv-cs-cv

arXiv:2605.14609v1 Announce Type: new Abstract: Accurate image segmentation remains challenging, particularly in generating sharp, confident boundaries. While modern architectures have advanced the fi

DiffusionOPD: A Unified Perspective of On-Policy Distillation in Diffusion Models

arXiv:2605.15055v1 Announce Type: cross Abstract: Reinforcement learning has emerged as a powerful tool for improving diffusion-based text-to-image models, but existing methods are largely limited to

safetyarxiv-cs-cv

Discovering Physical Directions in Weight Space: Composing Neural PDE Experts

model-releasesarxiv-cs-lg

arXiv:2605.14546v1 Announce Type: new Abstract: Recent advances in neural operators have made partial differential equation (PDE) surrogate modeling increasingly scalable and transferable through larg

Distribution-Aware Algorithm Design with LLM Agents

arXiv:2605.14141v1 Announce Type: new Abstract: We study learning when the learned object is executable solver code rather than a predictor. In this setting, correctness is not enough: two solvers may

Distribution Corrected Offline Data Distillation for Large Language Models

arXiv:2605.14071v1 Announce Type: new Abstract: Distilling reasoning traces from strong large language models into smaller ones is a promising route to improve intelligence in resource-constrained set

safetyarxiv-cs-cl

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving

arXiv:2507.04049v4 Announce Type: replace Abstract: Most end-to-end autonomous driving methods rely on imitation learning from single expert demonstrations, often leading to conservative and homogeneo

safetyarxiv-cs-cv

Do Coding Agents Understand Least-Privilege Authorization?

arXiv:2605.14859v1 Announce Type: cross Abstract: As coding agents gain access to shells, repositories, and user files, least-privilege authorization becomes a prerequisite for safe deployment: an age

Do Composed Image Retrieval Benchmarks Require Multimodal Composition?

arXiv:2605.14787v1 Announce Type: cross Abstract: Composed Image Retrieval (CIR) is a multimodal retrieval task where a query consists of a reference image and a textual modification, and the goal is

researcharxiv-cs-cl

Do Language Models Align with Brains? Prediction Scores Are Not Enough

arXiv:2605.14025v1 Announce Type: cross Abstract: Brain-language model comparisons often interpret neural prediction scores as evidence that model representations capture brain-relevant language compu

safetyarxiv-cs-ai

Agents

DriveCtrl: Conditioned Sim-to-Real Driving Video Generation

arXiv:2605.15116v1 Announce Type: new Abstract: Large-scale labelled driving video data is essential for training autonomous driving systems. Although simulation offers scalable and fully annotated da

agentsarxiv-cs-cv

Dual-Dimensional Consistency: Balancing Budget and Quality in Adaptive Inference-Time Scaling

arXiv:2605.15100v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable abilities in reasoning. However, maximizing their potential through inference-time scaling fac

Dual Hierarchical Dialogue Policy Learning for Legal Inquisitive Conversational Agents

arXiv:2605.14057v1 Announce Type: new Abstract: Most existing dialogue systems are user-driven, primarily designed to fulfill user requests. However, in many critical real-world scenarios, a conversat

safetyarxiv-cs-cl

DVMap: Fine-Grained Pluralistic Value Alignment via High-Consensus Demographic-Value Mapping

arXiv:2605.14420v1 Announce Type: new Abstract: Current Large Language Models (LLMs) typically rely on coarse-grained national labels for pluralistic value alignment. However, such macro-level supervi

Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signal

arXiv:2605.14014v1 Announce Type: cross Abstract: Internet of Things (IoT) systems continuously collect heterogeneous sensing signals from ubiquitous sensors to support intelligent applications such a

applicationsarxiv-cs-ai

Elastic Spiking Transformers for Efficient Gesture Understanding

arXiv:2605.13869v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs), particularly Spiking Transformers, offer energy-efficient processing of event-based sensor data for healthcare applica

Hardware

EMA: Efficient Model Adaptation for Learning-based Systems

arXiv:2605.13942v1 Announce Type: new Abstract: Machine learning (ML) is increasingly applied to optimize system performance in tasks such as resource management and network simulation. Unlike traditi

hardwarearxiv-cs-lg

Energy-Efficient Quadruped Locomotion with Compliant Feet

arXiv:2605.14411v1 Announce Type: cross Abstract: Quadruped robots are often designed with rigid feet to simplify control and maintain stable contact during locomotion. While this approach is straight

Eradicating Negative Transfer in Multi-Physics Foundation Models via Sparse Mixture-of-Experts Routing

arXiv:2605.15179v1 Announce Type: cross Abstract: Scaling Scientific Machine Learning (SciML) toward universal foundation models is bottlenecked by negative transfer: the simultaneous co-training of d

Explainable Detection of Depression Status Shifts from User Digital Traces

arXiv:2605.14995v1 Announce Type: new Abstract: Every day, users generate digital traces (e.g., social media posts, chats, and online interactions) that are inherently timestamped and may reflect aspe

Exploitation of Hidden Context in Dynamic Movement Forecasting: A Neural Network Journey from Recurrent to Graph Neural Networks and General Purpose Transformers

arXiv:2605.14855v1 Announce Type: cross Abstract: Forecasting within signal processing pipelines is crucial for mitigating delays, particularly in predicting the dynamic movements of objects such as N

Exploring Bottlenecks in VLM-LLM Navigation: How 3D Scene Understanding Capability Impacts Zero-Shot VLN

arXiv:2605.14801v1 Announce Type: new Abstract: Zero-shot vision-and-language navigation (VLN) has gained significant attention due to its minimal data collection costs and inherent generalization. Th

researcharxiv-cs-ro

Exploring Vision-Language Models for Online Signature Verification: A Zero-Shot Capability Study

model-releasesarxiv-cs-cv

arXiv:2605.14845v1 Announce Type: new Abstract: Recent advancements in Vision-Language Models (VLMs) have demonstrated strong capabilities in general visual reasoning, yet their applicability to rigor

FaceParts: Segmentation and Editing of Gaussian Splatting

arXiv:2605.13853v1 Announce Type: cross Abstract: Facial editing is an important task with applications in entertainment, virtual reality, and digital avatars. Most existing approaches rely on generat

FactNet: A Billion-Scale Knowledge Graph for Multilingual Factual Grounding

arXiv:2602.03417v2 Announce Type: replace Abstract: Large language models hallucinate factual claims and struggle to ground their outputs in retrievable evidence, particularly in non-English languages

researcharxiv-cs-cl

Hardware

FALO: Fast and Accurate LiDAR 3D Object Detection on Resource-Constrained Devices

arXiv:2506.04499v2 Announce Type: replace Abstract: Existing LiDAR 3D object detection methods predominantely rely on sparse convolutions and/or transformers, which can be challenging to run on resour

hardwarearxiv-cs-cv

Focused PU learning from imbalanced data

arXiv:2605.14467v1 Announce Type: new Abstract: We propose a new method of learning from positive and unlabeled (PU) examples in highly imbalanced datasets. Many real-world problems, such as disease g

applicationsarxiv-cs-lg

ForcingDAS: Unified and Robust Data Assimilation via Diffusion Forcing

arXiv:2605.14285v1 Announce Type: cross Abstract: Data assimilation (DA) estimates the state of an evolving dynamical system from noisy, partial observations, and is widely used in scientific simulati

applicationsarxiv-cs-lg

From Descriptive to Prescriptive: Uncover the Social Value Alignment of LLM-based Agents

arXiv:2605.14034v1 Announce Type: new Abstract: Wide applications of LLM-based agents require strong alignment with human social values. However, current works still exhibit deficiencies in self-cogni

From User Preferences to Base Score Extraction Functions in Gradual Argumentation (with Appendix)

arXiv:2602.14674v4 Announce Type: replace Abstract: Gradual argumentation is a field of symbolic AI which is attracting attention for its ability to support transparent and contestable AI systems. It

FU-MPC: Frontier- and Uncertainty-Aware Model Predictive Control for Efficient and Accurate UAV Exploration with Motorized LiDAR

arXiv:2605.14920v1 Announce Type: new Abstract: Efficient UAV exploration in unknown environments requires rapid coverage expansion while maintaining accurate and reliable localization, since safe nav

researcharxiv-cs-ro

Further Notes on Our Recent Research on AI Delegation and Long-Horizon Reliability

researchmicrosoft-research

Our recent paper, “LLMs Corrupt Your Documents When You Delegate”, has generated discussion about the reliability of AI systems in delegated workflows. We appreciate the interest in this work and want

Hardware

GenAI for Energy-Efficient and Interference-Aware Compressed Sensing of GNSS Signals on a Google Edge TPU

arXiv:2605.14839v1 Announce Type: new Abstract: Traditional methods for classifying global navigation satellite system (GNSS) jamming signals typically involve post-processing raw or spectral data str

hardwarearxiv-cs-lg