Search: “evaluation”

World Model Self-Distillation: Training World Models to Solve General Tasks

arXiv:2606.12072v1 Announce Type: new Abstract: Pretrained video generators are promising visual world models that exhibit emergent task-solving abilities; however, their reliance on detailed textual

11 Jun 2026

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A Bayesian Network Approach for Enhancing Security-Focused Decision Support Systems

DGX agent

arXiv:2606.10782v1 Announce Type: cross Abstract: The adoption and integration of heterogeneous stacks in most of today's open-source based networks brings clear benefits like interoperability and ava

tutorialsarxiv-cs-ai

10 Jun 2026

A Comprehensive Inference-Time Augmentation Framework in Physiological Signals: Application to PPG-Based AF Detection

arXiv:2606.10410v1 Announce Type: new Abstract: Objective: Accurate classification of physiological signals in real-world deployments is challenged by sensor noise, motion artifacts, and distribution

applicationsarxiv-cs-lg

A Constrained Natural-Language Interface for Variational Multi-Physics Finite Element Simulations in FEniCS

arXiv:2606.10928v1 Announce Type: cross Abstract: Large language models can reduce the manual effort required to set up finite element simulations, but they introduce reliability risks when generated

A Continuous-Time Markov Chain Framework for Insertion Language Models

arXiv:2606.10199v1 Announce Type: cross Abstract: Insertion Language Models (ILMs) offer several advantages over left-to-right generation and mask-based generation. However, existing formulations of i

researcharxiv-cs-cl

A Large Scale Open-Source Image and Video Dataset for Robust Wildfire Detection and Classification

arXiv:2606.10174v1 Announce Type: new Abstract: Wildfire detection and monitoring are critical for mitigating fire spread and reducing environmental and infrastructural damage. In this work, we introd

Local Ai

A Navigable Manifold of Hypothesized Consciousness-Spectrum States in Language Model Representations

arXiv:2606.09894v1 Announce Type: cross Abstract: Across contemplative, philosophical, and psychological accounts, human consciousness is often described along a similar spectrum, ranging from reactiv

local-aiarxiv-cs-cl

A Source Domain is All You Need: Source-Only Cross-OS Transfer Learning for APT Anomaly Detection via Semantic Alignment and Optimal Transport

arXiv:2606.10216v1 Announce Type: cross Abstract: Advanced Persistent Threats (APTs) are stealthy, multi-stage cyberattacks whose detection is difficult due to scarce labeled traces, severe class imba

Tutorials

A Unifying Lens on Supervised Fine-Tuning Through Target Distribution Design

arXiv:2606.11189v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) typically maximizes the likelihood of every token in a demonstrated trajectory. However, an observed token can be non-uni

tutorialsarxiv-cs-ai

ABC-Bench: An Agentic Bio-Capabilities Benchmark for Biosecurity

arXiv:2606.11150v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly acquiring capabilities relevant to biological research, from literature synthesis to interpretation of experime

Achieving Cloud-Grade SLOs for Local Mixture-of-Experts Inference through CPU-GPU Hybrid Design

arXiv:2606.10493v1 Announce Type: cross Abstract: Local deployment of large Mixture-of-Experts (MoE) models falls short of the service quality achieved in cloud-scale environments, even under low-conc

An Exposure-Time-Aligned Primary-Path Architecture for Autonomous-Driving ECUs

arXiv:2606.10856v1 Announce Type: new Abstract: While end-to-end (E2E) autonomous driving has become the dominant research direction, production vehicles continue to rely on modular multi-NN pipelines

agentsarxiv-cs-ro

Analyzing Training-Free Corruption Detection for Object Detection Datasets

arXiv:2606.10666v1 Announce Type: new Abstract: Annotation errors are widespread in computer vision datasets and can significantly degrade the performance of systems trained on them, particularly in c

applicationsarxiv-cs-cv

AnimaSpark: A Feed-Forward Method for Animating Arbitrary 3D Objects

arXiv:2606.10988v1 Announce Type: new Abstract: While recent advancements in generative AI have substantially accelerated static 3D model creation workflows, the synthesis of category-agnostic 3D anim

safetyarxiv-cs-cv

ArabiGEE: A Hierarchical Taxonomy for Arabic Grammatical Error Explanation

arXiv:2606.10765v1 Announce Type: new Abstract: We introduce ArabiGEE, the first comprehensive Arabic grammatical error explanation (GEE) taxonomy grounded in explicit error types. Unlike existing GEE

researcharxiv-cs-cl

As believers of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development 'Any topic related to buil…

model-releasesyann-lecun--x

As believers of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development 'Any topic related to building pretraining pipelines, distributed training infrastruct

Attention-Discounted Adaptive Sampler for Masked Diffusion Language Models

arXiv:2606.10829v1 Announce Type: cross Abstract: Masked diffusion language models can reduce inference steps by revealing multiple tokens per denoising iteration, but this parallelism is fragile: pos

Automatic Labelling for Low-Light Pedestrian Detection

arXiv:2507.02513v4 Announce Type: replace Abstract: Pedestrian detection in RGB images is a key task in pedestrian safety, as the most common sensor in autonomous vehicles and advanced driver assistan

safetyarxiv-cs-cv

AutoPDE: Reliable Agentic PDE Solving via Explicitly Represented Solver Strategies

arXiv:2606.10752v1 Announce Type: new Abstract: Numerical solvers for partial differential equations (PDEs) are core computational tools in science and engineering. Building reliable PDE solvers requi

agentsarxiv-cs-ai

BadRobot: Jailbreaking Embodied LLM Agents in the Physical World

arXiv:2407.20242v5 Announce Type: replace-cross Abstract: Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language und

Baseline-Free Policy Optimization for Neural Combinatorial Optimization

arXiv:2606.10321v1 Announce Type: cross Abstract: Neural combinatorial optimization (NCO) trains autoregressive policies to solve routing problems. The standard training algorithm, REINFORCE with a ro

Benchmarking stereo reconstruction for 3D printable Martian terrain models

arXiv:2606.10364v1 Announce Type: new Abstract: Reconstructing printable 3D models from Mars rover imagery is challenging because Martian terrain is low-texture, irregular, and partially observed. We

Beyond Explaining Predictions: Logic-Based Explanations for Confidence in Machine Learning Models

arXiv:2606.10347v1 Announce Type: new Abstract: Machine learning is increasingly used in critical domains, where both predictions and their associated confidence levels influence important decisions.

researcharxiv-cs-lg

Beyond Memorization: Distinguishing Between Pattern-Based and Epistemic Reasoning in LLMs Using Epistemic Puzzles

model-releasesarxiv-cs-cl

arXiv:2603.21350v2 Announce Type: replace Abstract: Epistemic reasoning requires agents to infer the state of the world from partial observations and information about other agents' knowledge. Prior w

Beyond Model Size: Probing the Gaps in Visual in-Context Learning by Training a Tiny Model

arXiv:2606.10905v1 Announce Type: new Abstract: Visual in-Context Learning (VICL) aims at making progress towards adaptive vision models, that can -- based on a few examples -- adapt to a new task at

Beyond Uniform Token-Level Trust Region in LLM Reinforcement Learning

arXiv:2606.10968v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become standard for improving LLM reasoning. However, existing PPO-style trust-region mechan

Bittensor Agent Arenas as a Trajectory Primitive: Distilling a Shopping Agent from ShoppingBench Subnet Traces

arXiv:2606.10064v1 Announce Type: cross Abstract: Small-model agentic post-training is bottlenecked less by the algorithm than by the trajectory substrate it consumes. Leading recipes (RLVR, group-rel

Boosting ECG Classification Performance by Pre-training with Synthesized Data

arXiv:2606.10802v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) typically require extensive datasets for effective training. In the medical domain, acquiring large-scale data is often ch

applicationsarxiv-cs-ai

Bridging Semantics and Physical Execution: A Neuro-Symbolic Framework for Multi-Pair Robotic Assembly

arXiv:2606.10808v1 Announce Type: new Abstract: Multi-pair robotic assembly in unstructured environments faces spatial interference and contact uncertainties. Existing paradigms fail to bridge cogniti

agentsarxiv-cs-ro

Building Change Detection in Earthquake: A Multi-Scale Interaction Network and A Change Detection Dataset

arXiv:2606.10329v1 Announce Type: cross Abstract: As one of the most destructive natural disasters, earthquakes have struck many countries around the world in recent years, causing serious economic lo

Business World Model

arXiv:2606.10044v1 Announce Type: new Abstract: Businesses are increasingly adopting AI-enabled tools to improve productivity, reduce costs, and enhance products and services. However, the transformat

agentsarxiv-cs-ai

Can Image Models Imagine Time? ImageTime: A Novel Benchmark for Probing Visual World Modeling Through Spatiotemporal Consistency

arXiv:2606.10620v1 Announce Type: cross Abstract: Image generation models now produce high-quality static images, yet their ability to represent how a visual world changes over time remains poorly und

Can Multi-Agent LLMs Identify Their Peers? Stylometric Fingerprinting in Role-Constrained Political Analysis

arXiv:2606.09854v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) pipelines for political statement analysis are vulnerable to peer-preservation bias: models tend to protect pee

Can we trust our models? Epistemic calibration in second-order classification

arXiv:2606.10777v1 Announce Type: new Abstract: Uncertainty estimation is critical for deploying machine learning models in high-stakes settings. However, classical calibration only assesses the relia

researcharxiv-cs-lg

CANVAS: Captioning Art with Narrative Visual-Audio AI Systems

arXiv:2606.09846v1 Announce Type: cross Abstract: Visual art remains largely inaccessible to blind and low-vision (BLV) audiences due to brief or absent alt-text, which rarely conveys the sensory, spa

applicationsarxiv-cs-ai

CIAware-Bench: Benchmarking Control Intervention Awareness Across Frontier LLMs

arXiv:2606.11063v1 Announce Type: new Abstract: AI control protocols oversee untrusted models by monitoring their actions and modifying potentially unsafe steps, often using a trusted model. This part

CleanPatrick: A Benchmark for Image Data Cleaning

arXiv:2505.11034v2 Announce Type: replace-cross Abstract: Robust machine learning depends on clean data, yet current image data cleaning benchmarks rely on synthetic noise or narrow human studies, lim

ClinReadNet: A clinical reading-inspired network for low-dose abdominal CT image quality assessment

arXiv:2606.10372v1 Announce Type: new Abstract: In abdominal CT imaging, developing a low-dose, no-reference image quality assessment (No-reference IQA) model that mimics doctors' reading habits for e

researcharxiv-cs-cv

Closing the Modality Gap in Zero-Shot HAR: Contrastive Training and Separability-Optimized Prototypes on IMU Data

arXiv:2606.10789v1 Announce Type: new Abstract: Zero-shot learning (ZSL) for inertial measurement unit (IMU)-based human activity recognition (HAR) faces a central challenge: bridging the gap between

safetyarxiv-cs-lg

Local Ai

COGENT: Continuous Graph Emulators with Neural Ordinary Differential Equations for Long-Term Physical Forecasting

arXiv:2606.11162v1 Announce Type: new Abstract: In this work, we present COGENT, a continuous graph emulator with Neural Ordinary Differential Equations for long-term physical forecasting on irregular

local-aiarxiv-cs-lg

Compile Once, Differentiate Everywhere: A Differentiable Meta-Circular Interpreter

model-releasesarxiv-cs-lg

arXiv:2606.09930v1 Announce Type: cross Abstract: The boundary between program execution and gradient-based optimization has long limited the use of code itself as a learnable scientific model. We pre

Conformal Risk Prediction for Non-Alcoholic Fatty Liver Disease Using Gradient Boosting with Distribution-Free Coverages

arXiv:2606.09860v1 Announce Type: cross Abstract: Non-alcoholic fatty liver disease (NAFLD) affects roughly 25% of global adults, posing substantial hepatic and cardiovascular risks. Yet, population-l

Convergence of Monte Carlo Optimistic Policy Iteration: Beyond Uniform State-Action Updates

arXiv:2606.10580v1 Announce Type: cross Abstract: The asymptotic behaviour of Monte Carlo optimistic policy iteration (MC-O-PI) is a long-standing open question. When the model of the environment is u

Cyst-X: A Multi-Center MRI Benchmark and Federated Learning Framework for Malignancy-Risk Stratification of Pancreatic Cystic Neoplasm

arXiv:2507.22017v4 Announce Type: replace-cross Abstract: Pancreatic cancer is projected to be the second-deadliest cancer by 2030, making early detection critical. Intraductal papillary mucinous neop

DAH-Net: A Dual-Attention Hybrid Network for Interpretable and Robust EEG-Based Emotion Recognition

arXiv:2602.06411v2 Announce Type: replace Abstract: EEG-based emotion recognition supports affective brain-computer interfaces and mental health monitoring yet remains challenged by signal complexity,

researcharxiv-cs-lg

Data assimilation for subsurface flow using latent diffusion model parameterization: performance of ensemble-Kalman and Monte Carlo techniques

arXiv:2606.11140v1 Announce Type: cross Abstract: Data assimilation (DA) in subsurface flow entails calibrating model parameters to match observed data, typically at wells, while preserving geological

Data-Driven Dynamic Assortment in Online Platforms: Learning about Two Sides

model-releasesarxiv-cs-lg

arXiv:2606.11118v1 Announce Type: new Abstract: We study a dynamic assortment problem on a two-sided service platform with incomplete information and heterogeneous customers in a discrete-time setting

Data-Driven Runway and Taxiway Exits Prediction of Landing Aircraft: A Case Study at Hartsfield-Jackson Atlanta International Airport

model-releasesarxiv-cs-lg

arXiv:2606.11017v1 Announce Type: new Abstract: Airport surface operations increasingly constrain performance at high-throughput hubs. This study examines arrival taxi-in decisions at Hartsfield-Jacks