arXiv:2609.21386v1 Announce Type: cross Abstract: Comprehensive video understanding is crucial for advancing artificial intelligence toward the intricate…
Tag: AI
Consistent Relexicalization of Clinical Documents using Graph-Based Approach
arXiv:2609.21387v1 Announce Type: cross Abstract: Relexicalization is a pivotal technique in clinical NLP, as it facilitates robust masking of sensitive…
From Memory to Behavior: A Behavior-Aware Role-Playing Framework for Social Media Influencers
arXiv:2609.21349v1 Announce Type: cross Abstract: Large language models have shown strong potential as role-playing agents for real individuals, yet…
Knowledge-Graph-Augmented Chronos-2 for HEC-RAS Surrogate Forecasting
arXiv:2609.21381v1 Announce Type: cross Abstract: We investigate whether coupling a time-series foundation model to hydraulic project knowledge improves…
Here’s What Nobody’s Telling the Middle Class About AI
I’ve spent most of my career around people who work with their hands, including the electricians and warehouse workers who show up at 5 a.m. and don’t…
WS-NeRF: A Mamba-Driven World-State-Aware Adaptive Deblurring Neural Radiance Field
arXiv:2609.21391v1 Announce Type: cross Abstract: Neural Radiance Fields (NeRF) have attracted extensive attention in recent years due to their strong…
Authorization Revocation for Long-Running AI Agents: Root-Scoped Quiescence under Delegation and Asynchronous Execution
arXiv:2609.21284v1 Announce Type: cross Abstract: Long-running AI agents outlive initiating processes through credentials, delegated tasks, queues,…
CESBench: Benchmarking Large Language Models on Cryptographic Engineering Security for IoT Devices
arXiv:2609.21344v1 Announce Type: cross Abstract: For Internet of Things (IoT) devices, a secure algorithm alone is not enough: an attacker with physical…
Deep Reinforcement Learning with Buffered Quantile Objectives
arXiv:2609.21327v1 Announce Type: cross Abstract: Quantile-based reinforcement learning provides an interpretable approach to risk-sensitive…
Co-Evolving Zero-Day Jamming: Adaptive Attack Synthesis and Graph Attention-Based Online Detection
arXiv:2609.21334v1 Announce Type: cross Abstract: Effective evaluation of zero-day jamming detectors requires robust adversarial models. However, existing…