Search: “evaluation”

Towards Systematic Generalization for Power Grid Optimization Problems

arXiv:2605.02026v1 Announce Type: new Abstract: AC Optimal Power Flow (ACOPF) and Security-Constrained Unit Commitment (SCUC) are fundamental optimization problems in power system operations. ACOPF se

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Training Non-Differentiable Networks via Optimal Transport

DGX agent

arXiv:2605.01928v1 Announce Type: new Abstract: Neural networks increasingly embed non-differentiable components (spiking neurons, quantized layers, discrete routing, blackbox simulators, etc.) where

safetyarxiv-cs-lg

5 May 2026

Ultrasound Vision-Language Alignment via Contrastive Learning

arXiv:2605.02126v1 Announce Type: new Abstract: Ultrasound foundation models have achieved strong performance on structured prediction tasks but remain exclusively vision-based, limiting zero-shot and

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Unsupervised Learning of Robust Spectral Shape Matching

arXiv:2304.14419v2 Announce Type: replace Abstract: We propose a novel learning-based approach for robust 3D shape matching. Our method builds upon deep functional maps and can be trained in a fully u

Validation of an AI-based end-to-end model for prostate pathology using long-term archived routine samples

arXiv:2605.02614v1 Announce Type: new Abstract: Artificial intelligence (AI) is becoming a clinical tool for prostate pathology, but generalization across variations in sample preparation and preserva

Validation of Whole-Slide Foundation Models for Image Retrieval in TCGA Data

arXiv:2605.00902v1 Announce Type: new Abstract: Foundation models are reshaping computational histopathology, yet their value for whole-slide image retrieval relative to strong patch-based and supervi

VILAS: A VLA-Integrated Low-cost Architecture with Soft Grasping for Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2605.02037v1 Announce Type: new Abstract: We present VILAS, a fully low-cost, modular robotic manipulation platform designed to support end-to-end vision-language-action (VLA) policy learning an

Visual Chart Representations for Cryptocurrency Regime Prediction: A Systematic Deep Learning Study

arXiv:2605.00875v1 Announce Type: new Abstract: Technical traders have long relied on visual analysis of candlestick charts to identify market patterns and predict price movements. While deep learning

Visualizing Critic Match Loss Landscapes for Interpretation of Online Reinforcement Learning Control Algorithms

model-releasesarxiv-cs-lg

arXiv:2603.14535v2 Announce Type: replace Abstract: Reinforcement learning has proven its power on various occasions. However, its performance is not always guaranteed when system dynamics change. Ins

VOFA: Visual Object Goal Pushing with Force-Adaptive Control for Humanoids

arXiv:2605.01518v1 Announce Type: new Abstract: The ability to push large objects in a goal-directed manner using onboard egocentric perception is an essential skill for humanoid robots to perform com

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VRGaussianAvatar: Integrating 3D Gaussian Avatars into VR

arXiv:2602.01674v2 Announce Type: replace Abstract: We present VRGaussianAvatar, an integrated system that enables real-time full-body 3D Gaussian Splatting (3DGS) avatars in virtual reality using onl

Watch Your Step: Information Injection in Diffusion Models via Shadow Timestep Embedding

arXiv:2605.00935v1 Announce Type: cross Abstract: Diffusion models have become the foundation of modern generative systems, with most research focusing primarily on improving generation efficiency and

What Does a Meow Mean? In Search of Intuitively Understandable Communication by a Nonverbal Companion Robot

arXiv:2605.01251v1 Announce Type: cross Abstract: Older adults living alone have a number of challenges, and robots can help with some of them--by providing reminders, initiating activity, or offering

researcharxiv-cs-ro

When Correct Isn't Usable: Improving Structured Output Reliability in Small Language Models

model-releasesarxiv-cs-cl

arXiv:2605.02363v1 Announce Type: new Abstract: Deployed language models must produce outputs that are both correct and format-compliant. We study this structured-output reliability gap using two math

When Good OCR Is Not Enough: Benchmarking OCR Robustness for Retrieval-Augmented Generation

arXiv:2605.00911v1 Announce Type: new Abstract: Industrial Retrieval-Augmented Generation (RAG) systems depend on optical character recognition (OCR) to transform visual documents into text. Existing

When To Adapt? Adapting the Model or Data in Federated Medical Imaging

arXiv:2605.00892v1 Announce Type: new Abstract: Federated learning enables collaborative model training across medical institutions without sharing raw data, but its performance is often limited by do

Who Decides What Is Harmful? Content Moderation Policy Through A Multi-Agent Personalised Inference Framework

arXiv:2605.01416v1 Announce Type: cross Abstract: The increasing scale and complexity of online platforms raises critical policy questions around harmful content, digital well-being, and user autonomy

safetyarxiv-cs-cl

X2SAM: Any Segmentation in Images and Videos

arXiv:2605.00891v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong image-level visual understanding and reasoning, yet their pixel-level perception acros

Tutorials

XekRung Technical Report

arXiv:2605.00072v1 Announce Type: cross Abstract: We present XekRung, a frontier large language model for cybersecurity, designed to provide comprehensive security capabilities. To achieve this, we de

tutorialsarxiv-cs-ai

2D-SuGaR: Surface-Aware Gaussian Splatting for Geometrically Accurate Mesh Reconstruction

arXiv:2605.00569v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for generating photorealistic renderings of a scene in real-time. However, the volumetr

A Comparative Study of UMAP and Other Dimensionality Reduction Methods

arXiv:2603.02275v2 Announce Type: replace Abstract: Uniform Manifold Approximation and Projection (UMAP) is a widely used manifold learning technique for dimensionality reduction. This paper studies U

Adaptive Equilibrium: Dynamic Weighting Framework for Generalized Interruption of DeepFake Models

arXiv:2605.00443v1 Announce Type: cross Abstract: The advancement of generalized deepfake disruption is constrained by the interruption imbalance, a fundamental bottleneck inherent to the generation o

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Adaptive Geodesic Conformal Prediction for Egocentric Camera Pose Estimation

arXiv:2605.00233v1 Announce Type: new Abstract: Egocentric pose estimation for Augmented Reality (AR) and assistive devices requires not just accurate predictions but guaranteed uncertainty regions. C

Adaptive Norm-Based Regularization for Neural Networks

arXiv:2605.00171v1 Announce Type: cross Abstract: In this paper, we study norm-based regularization methods for neural networks. We compare existing penalization approaches and introduce two regulariz

Agent Factories for High Level Synthesis: How Far Can General-Purpose Coding Agents Go in Hardware Optimization?

model-releasesarxiv-cs-lg

arXiv:2603.25719v2 Announce Type: replace-cross Abstract: We present an empirical study of how far general-purpose coding agents -- without hardware-specific training -- can optimize hardware designs

Agents

Agent-guided workflows to accelerate model customization in Amazon SageMaker AI

Amazon SageMaker AI now offers an agentic experience that changes this. Developers describe their use case using natural language, and the AI coding agent streamlines the entire journey, from use case

agentsaws-ml-blog

Alethia: A Foundational Encoder for Voice Deepfakes

model-releasesarxiv-cs-cl

arXiv:2605.00251v1 Announce Type: cross Abstract: Existing voice deepfake detection and localization models rely heavily on representations extracted from speech foundation models (SFMs). However, dow

Agents

An End-to-End Decision-Aware Multi-Scale Attention-Based Model for Explainable Autonomous Driving

arXiv:2605.00291v1 Announce Type: new Abstract: The application of computer vision is gradually increasing across various domains. They employ deep learning models with a black-box nature. Without the

agentsarxiv-cs-cv

Applications

Are You the A-hole? A Fair, Multi-Perspective Ethical Reasoning Framework

arXiv:2605.00270v1 Announce Type: new Abstract: Standard methods for aggregating natural language judgments, such as majority voting, often fail to produce logically consistent results when applied to

applicationsarxiv-cs-cl

Applications

Autoformalizing Memory Specifications with Agents

arXiv:2605.00058v1 Announce Type: cross Abstract: The primary goal of Design Verification (DV) is to ensure that a proposed chip design implementation (either in code, or physical form) exactly matche

applicationsarxiv-cs-lg

Beyond Decodability: Reconstructing Language Model Representations with an Encoding Probe

arXiv:2605.00607v1 Announce Type: new Abstract: Probing is widely used to study which features can be decoded from language model representations. However, the common decoding probe approach has two l

researcharxiv-cs-cl

Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts

arXiv:2508.06361v4 Announce Type: replace Abstract: Large Language Models (LLMs) are widely deployed in reasoning, planning, and decision-making tasks, making their trustworthiness critical. A signifi

safetyarxiv-cs-lg

Brain MR Image Synthesis with 3D Multi-Contrast Self-Attention GAN

arXiv:2604.00070v2 Announce Type: replace-cross Abstract: Complete and high-quality multi-modal Magnetic Resonance Imaging (MRI) is essential for accurate neuro-oncological assessment, as each contras

Budget-Aware Routing for Long Clinical Text

arXiv:2605.00336v1 Announce Type: new Abstract: A key challenge for large language models is token cost per query and overall deployment cost. Clinical inputs are long, heterogeneous, and often redund

researcharxiv-cs-cl

Caracal: Causal Architecture via Spectral Mixing

model-releasesarxiv-cs-lg

arXiv:2605.00292v1 Announce Type: new Abstract: The scalability of Large Language Models to long sequences is hindered by the quadratic cost of attention and the limitations of positional encodings. T

Agents

Causality-enhanced Decision-Making for Autonomous Mobile Robots in Dynamic Environments

arXiv:2504.11901v5 Announce Type: replace Abstract: The growing integration of robots in shared environments-such as warehouses, shopping centres, and hospitals-demands a deep understanding of the und

agentsarxiv-cs-ro

Certifiable Factor Graph Optimization

arXiv:2603.01267v2 Announce Type: replace-cross Abstract: We show that the factor graph and certifiable estimation paradigms, which have thus far been treated as essentially independent in the literat

claudely: launch Claude Code against Local LLM provider like LM Studio / Ollama / llama.cpp without trashing your real claude config

claudely is a tool that enables users to run Claude Code against local LLM providers such as LM Studio, Ollama, or llama.cpp while preserving their existing Claude configuration. The tool allows devel

model-releasesr-ollama

Combined Dictionary Unfolding Network with Gradient-Adaptive Fidelity for Transferable Multi-Source Fusion

arXiv:2605.00461v1 Announce Type: cross Abstract: Deep Unfolding Network-based methods have emerged as effective solutions for multi-source image fusion by combining model-driven iterative optimizatio

Conformalized Quantum DeepONet Ensembles for Scalable Operator Learning with Distribution-Free Uncertainty

arXiv:2605.00330v1 Announce Type: new Abstract: Operator learning enables fast surrogate modeling of high-dimensional dynamical systems, but existing approaches face two fundamental limitations: quadr

safetyarxiv-cs-lg

ControBench: An Interaction-Aware Benchmark for Controversial Discourse Analysis on Social Networks

model-releasesarxiv-cs-cl

arXiv:2605.00513v1 Announce Type: new Abstract: Understanding how people argue across ideological divides online is important for studying political polarization, misinformation, and content moderatio

CRADIPOR: Crash Dispersion Predictor

arXiv:2605.00070v1 Announce Type: new Abstract: We present CRADIPOR, a numerical dispersion prediction tool for automotive crash simulations. Finite Element (FE) crash models are widely used throughou

CURE-OOD: Benchmarking Out-of-Distribution Detection for Survival Prediction

arXiv:2605.00350v1 Announce Type: new Abstract: ``How long can I live and remain free of cancer?'' is often the first question a patient asks after receiving a cancer diagnosis and treatment. Accurate

Decentralized Proximal Stochastic Gradient Langevin Dynamics

arXiv:2605.00723v1 Announce Type: cross Abstract: We propose Decentralized Proximal Stochastic Gradient Langevin Dynamics (DE-PSGLD), a decentralized Markov chain Monte Carlo (MCMC) algorithm for samp

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Deepfakes: we need to re-think the concept of 'real' images

arXiv:2509.21864v2 Announce Type: replace Abstract: The wide availability and low usability barrier of modern image generation models has triggered the reasonable fear of criminal misconduct and negat

Distance-Aware Error for Spline Networks: A Bottom-Up Approach to Uncertainty

arXiv:2501.04757v2 Announce Type: replace-cross Abstract: We develop a new class of distance-aware error bounds that tightly characterize the approximation error of spline neural networks. Our bottom-

Diversity in Large Language Models under Supervised Fine-Tuning

arXiv:2605.00195v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) is essential for aligning Large Language Models (LLMs) with user intent, yet it is believed to suppress generative diversit

Tutorials

Doubly robust identification of treatment effects from multiple environments

arXiv:2503.14459v2 Announce Type: replace-cross Abstract: Practical and ethical constraints often require the use of observational data for causal inference, particularly in medicine and social scienc

tutorialsarxiv-cs-lg