Search: “evaluation”

Myopia Prevention and Control 3.0: Artificial Intelligence--Driven Risk Stratification, Proactive Monitoring, and Personalized Intervention

arXiv:2607.24187v1 Announce Type: new Abstract: The convergence of artificial intelligence (AI), digital sensing, and ubiquitous computing has created an unprecedented opportunity to transform myopia

researcharxiv-cs-ai

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Research

N_0-TWAM: Scaling Tactile-Native World-Action Model for Contact-Rich Manipulation

DGX agent

arXiv:2607.23783v1 Announce Type: new Abstract: We present N_0-TWAM, a tactile-native world-action model for contact-rich manipulation that predicts both future vision and future contact. To our knowl

researcharxiv-cs-ro

28 Jul 2026

Nearly Tight Bounds for Cross-Learning Contextual Bandits with Graphical Feedback

arXiv:2502.04678v2 Announce Type: replace Abstract: Repeated first-price auctions are contextual decision problems with censored but reusable feedback: after submitting a bid, a learner can infer the

NEO: NeRF It Once, Edit It Many Times for Continuous Object Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.24538v1 Announce Type: new Abstract: In this paper, we present NEO, a unified framework providing language-guided NeRF editing for robotic manipulation. Our paper introduces (i) a language-

Neural Representation of Minimal Surfaces

arXiv:2607.23437v1 Announce Type: cross Abstract: We propose a neural representation for minimal surfaces. Unlike prior approaches based on discretization or Physics-Informed Neural Networks (PINNs),

Not All LLM Reasoning is Visible in the Chain-of-Thought

arXiv:2607.22925v1 Announce Type: cross Abstract: A key question for AI safety is whether a language model expresses all of its reasoning in its output tokens. We demonstrate a concrete failure mode w

Nova3D: Code-Native Generation of Programmable 3D Assets

model-releasesarxiv-cs-cv

arXiv:2607.22738v1 Announce Type: cross Abstract: Current 3D generative models mostly produce a final surface: a visually strong but largely opaque mesh. Interactive 3D worlds need more than a surface

Obliviate: Efficient Unlearning in Recommender Systems

arXiv:2607.22665v1 Announce Type: new Abstract: Machine unlearning is becoming increasingly critical in the context of data privacy regulations, particularly for recommendation systems that are direct

researcharxiv-cs-ai

Occluded Oculus: Operationalizing Stylistic Obscurement

arXiv:2607.24411v1 Announce Type: cross Abstract: What did it take for Hermes, the devout messenger of the Olympian gods, to slay Argus Panoptes, the multi-eyed giant of Greek myth? As the perfect gua

researcharxiv-cs-cl

Occlusion-Point Reuse for Ray-Traced Ambient Occlusion and Shadow

arXiv:2607.23122v1 Announce Type: cross Abstract: Ambient occlusion (AO) and soft shadows are critical visibility cues for spatial perception in real-time rendering. Hardware ray tracing provides a di

OmniCache: Multidimensional Hierarchical Feature Caching For Diffusion Models

arXiv:2607.23844v1 Announce Type: new Abstract: High-resolution image and video diffusion models, including SD3, FLUX, and recent video diffusion transformers, have substantially improved generative q

Online Fair Division with Budget Constraints

arXiv:2607.23310v1 Announce Type: cross Abstract: We study an online variant of discrete fair division under generalized assignment budget constraints. Goods arrive one at a time and must be assigned

Optimal Reward Shaping: Autonomous Car Parking Case Study

arXiv:2607.23617v1 Announce Type: new Abstract: Designing effective reward functions for model-free reinforcement learning under non-holonomic constraints remains a persistent challenge, often resulti

safetyarxiv-cs-lg

Order in Desbordante: Techniques for Efficient Implementation of Order Dependency Discovery Algorithms

arXiv:2607.23632v1 Announce Type: cross Abstract: Science-intensive data profiling focuses on discovery and validation of various patterns in datasets. This study considers discovery of one such patte

researcharxiv-cs-ai

Panda: Unsupervised Pelvic Anomaly Detection for Real-Time MR Imaging

arXiv:2607.24703v1 Announce Type: new Abstract: Female pelvic diseases remain an under researched area characterized by often delayed diagnosis. While pelvic MRI offers superior soft-tissue contrast f

PANOPTICON: A PII-Based Assemblage of Naturalistic Output Tokens for Investigating Privacy Leakage Within LLM Context Window

arXiv:2607.22695v1 Announce Type: new Abstract: Large Language Models (LLMs) are capable of generalizing human language for the completion of never-before-seen tasks, leading to widespread deployment.

Parallel Swin Transformer-Enhanced 3D MRI-to-CT Synthesis for MRI-Only Radiotherapy Planning

arXiv:2602.05387v2 Announce Type: replace Abstract: MRI provides superior soft tissue contrast without ionizing radiation; however, the absence of electron density information limits its direct use fo

Parallel Tokenizers: Rethinking Encoder Models' Vocabulary Design in Cross-Lingual Transfer of Low-Resource Languages

arXiv:2510.06128v2 Announce Type: replace Abstract: Tokenization forms the basis of multilingual language models, yet existing methods often limit cross-lingual transfer by mapping semantically equiva

safetyarxiv-cs-cl

Tutorials

Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration

arXiv:2607.23343v1 Announce Type: cross Abstract: Intraoperative 2D/3D registration aligns preoperative CT volumes with intraoperative X-ray or fluoroscopic images and is essential for image-guided in

tutorialsarxiv-cs-ai

PerturbPFN: Probing the Limits of Synthetic Priors in Drug Perturbation Modelling

arXiv:2607.23447v1 Announce Type: new Abstract: Predicting cellular responses to unseen chemical perturbations is challenging due to unknown targets and mechanisms, high-dimensional expression respons

Photonic reservoir computing with complex networks

arXiv:2607.23285v1 Announce Type: cross Abstract: Photonic reservoir computing has attracted increasing attention as a fast and low-cost approach for time-series prediction. Photonic reservoir computi

PIRL: From Open-Loop Exploration to Closed-Loop Reinforcement Learning [R]

local-air-machinelearning

TL;DR: Most RL post-training algorithms optimize the current batch and move on. But after an update, did the new policy actually become better? We introduce Policy Improvement Reinforcement Learning (

Pointer-Augmented Autoregressive Generation of Patent Claims with Joint Topology and Content Decoding

model-releasesarxiv-cs-cl

arXiv:2607.24040v1 Announce Type: new Abstract: Autoregressive decoders emit flat token sequences and cannot enforce hierarchical constraints across output segments, a limitation that becomes acute in

Poison to Detect: Detection of Targeted Overfitting in Federated Learning

arXiv:2509.11974v3 Announce Type: replace-cross Abstract: Federated Learning (FL) enables collaborative model training among clients without centralising data, making it a widely adopted privacy-enhan

Pose-Aware Modeling to Mitigate Pose-Related Artifacts in Tactile Gloves

arXiv:2607.22964v1 Announce Type: new Abstract: Tactile gloves digitize contact and force during hand-object interactions, enabling robotics applications in dexterous manipulation, teleoperation, and

researcharxiv-cs-ro

QFedPolyp: A Communication- and Inference-Efficient Federated Learning Framework for Polyp Segmentation

arXiv:2607.22743v1 Announce Type: cross Abstract: Background and Objective: Automatic polyp segmentation supports computer-aided diagnosis and early colorectal cancer detec- tion. Centralized deep lea

Quality-Adaptive Multi-UAV 3D Reconstruction with Sparse Workload Redistribution

arXiv:2607.24233v1 Announce Type: new Abstract: 3D reconstruction of unknown environments is a key application in robotics but is severely limited by the computational and energy capabilities of curre

researcharxiv-cs-ro

Hardware

Real-Time Semantic Segmentation with Optimized RetinaNet Architectures for Embedded Automotive Systems

arXiv:2607.22714v1 Announce Type: cross Abstract: Real-time perception is a foundational requirement for advanced driver assistance systems (ADAS) and autonomous vehicles, yet embedded automotive plat

hardwarearxiv-cs-ai

Reality Monitoring in Large Language Models: Self-Knowledge That Transforms with Conversation Memory

arXiv:2607.23927v1 Announce Type: new Abstract: A conversational AI that cannot tell its own output from what a user said will treat its own mistakes as user-provided facts. In humans, this capacity i

Agents

ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System

arXiv:2607.14178v2 Announce Type: replace Abstract: Recent advances in Large Language Models have fueled autonomous AI agents capable of tackling complex scientific tasks, yet existing automated resea

agentsarxiv-cs-ai

Reason Popper-ly: Patching In-Context Reasoning with Inductive Logic Programming

arXiv:2607.23019v1 Announce Type: new Abstract: Chain-of-thought (CoT) prompting enables large language models (LLMs) to tackle multi-step reasoning tasks, yet the generated intermediate steps are not

Reasoning or Memorization: Can LLMs Understand and Generate Chinese Xiehouyu Riddles?

arXiv:2607.23440v1 Announce Type: cross Abstract: In this paper, we push the boundary of LLM reasoning by testing them in a Chinese language game, xiehouyu, with novel xiehouyu created by linguists th

Reconstruction of SINR Maps from Sparse Measurements using Group Equivariant Non-Expansive Operators

arXiv:2507.19349v3 Announce Type: replace Abstract: As sixth generation (6G) wireless networks evolve, accurate signal-to-interference-noise ratio (SINR) maps are becoming increasingly critical for ef

safetyarxiv-cs-lg

ReflexTrack: A Feedback-Driven Agent for Training-Free Referring Video Object Segmentation

arXiv:2607.24098v1 Announce Type: new Abstract: Referring video object segmentation (RVOS) requires segmenting a target specified by natural language throughout a video. Recent agentic approaches comb

local-aiarxiv-cs-cv

Reinforcement Learning for Heterogeneous Sensor Selection in Maritime Surveillance

arXiv:2607.22667v1 Announce Type: new Abstract: This paper presents an information-gain-guided reinforcement-learning sensor-selection framework for single-vessel tracking in heterogeneous maritime se

safetyarxiv-cs-ai

Robust 6-DoF Object Pose Tracking with Built-In Recovery under Occlusions and Rapid Object Motions

arXiv:2607.23468v1 Announce Type: new Abstract: Real-time 6-DoF object pose tracking is essential for many robotics applications, and several approaches exist. Yet even today's approaches remain unrel

safetyarxiv-cs-cv

SADe: Sparse-Atom Support Decontamination for Few-Shot Segmentation with Weak Support Annotations

arXiv:2607.24706v1 Announce Type: new Abstract: Few-shot segmentation (FSS) commonly assumes clean pixel-level support masks, yet practical support supervision often uses boxes, scribbles, coarse mask

SafeCRS: Personalized Safety Alignment for LLM-Based Conversational Recommender Systems

arXiv:2603.03536v2 Announce Type: replace-cross Abstract: Current LLM-based conversational recommender systems (CRS) primarily optimize recommendation accuracy and user satisfaction. We identify an un

Schema-Aware Localisation (SAL): Live Schema Grounding and Hallucination Validation for Oracle NL2SQL

arXiv:2607.22572v1 Announce Type: new Abstract: Large language models can generate fluent SQL from natural language, but on real enterprise Oracle databases they frequently fail at execution time: col

scMIR: a vision-language foundation model for single-cell light microscopy image representation

arXiv:2607.22712v1 Announce Type: cross Abstract: Single-cell light microscopy images have become an important data source for characterizing cell phenotypes, but their complexity and heterogeneity po

SechKAN: Kolmogorov-Arnold Networks with Hyperbolic Secant Functions

arXiv:2607.18290v2 Announce Type: replace-cross Abstract: In recent years, Kolmogorov-Arnold Networks (KANs) have attracted increasing attention due to their effectiveness in machine learning and scie

Segmentation Robustness and Predictive Utility in Glioblastoma Radiomics: Evidence for a Trade-off in Survival Modelling

arXiv:2607.23626v1 Announce Type: cross Abstract: Radiomic biomarkers derived from magnetic resonance imaging (MRI) have been widely investigated as non-invasive tools for tumor characterization and p

Self-Authored Verification Is Unreliable in Heuristic Self-Improving Agents

arXiv:2607.24300v1 Announce Type: new Abstract: Self-improving agents accumulate capability by repeatedly rewriting procedural policies, controllers, or heuristic rules. They typically rely on self-au

safetyarxiv-cs-cl

Self-Motivated Growing Neural Network for Adaptive Architecture via Local Structural Plasticity

arXiv:2512.12713v2 Announce Type: replace-cross Abstract: Control policies are often implemented with fixed-capacity multilayer perceptrons trained by backpropagation, which require architecture selec

safetyarxiv-cs-lg

Applications

Semantic Semi-Incremental Data-Association-Free Object SLAM

arXiv:2607.23384v1 Announce Type: cross Abstract: Data association between landmark measurements and landmark variables has long been a central challenge in SLAM, as estimation accuracy depends critic

applicationsarxiv-cs-ai

SHARE: Towards Head-Mounted AR with User-Centric SLAM in Shared Human-Robot Workspaces

arXiv:2607.23901v1 Announce Type: cross Abstract: Human-Robot Collaboration (HRC) in shared physical spaces using Augmented Reality (AR) interfaces is powered by Simultaneous Localization and Mapping

local-aiarxiv-cs-ro

Shift-Aware Calibration for Fine-Tuned CLIP: Leveraging Image-Text Alignment

arXiv:2501.19060v4 Announce Type: replace Abstract: Vision-language models (VLMs), such as CLIP, adapt effectively to downstream tasks through prompt tuning, but fine-tuning can misalign predictive co

safetyarxiv-cs-cv

Simulating Tenant Responses to Energy Policy Interventions with Transaction-Cost-Aware LLM Age

arXiv:2607.24341v1 Announce Type: new Abstract: Recent studies use Large language models (LLMs) to simulate human opinions and decisions by prompting models with demographic, attitudinal, or persona-b