The paper introduces WaspMOT, a new benchmark for long-term multi-object tracking, and evaluates five tracking-by-detection methods.

The paper introduces RoboWits, a new bi-manual robotic benchmark designed to test a robot's cognitive reasoning and adaptability to unexpected challenges, revealing that current Vision-Language-Action…

The paper proposes a lightweight, passive bot detection system using user-agent and favicon analysis on web server logs, achieving 67.7% bot detection with a low 3% false-positive rate.

The paper introduces the Task Alignment Benchmark (TAB) to evaluate terminal agents' ability to selectively follow relevant environmental instructions while ignoring misleading distractors, revealing…

This paper proposes SpikingMOT, a spike-driven multi-object tracking system that uses spiking neural networks and adaptively models sparse trajectory dynamics.

WebTrap introduces a stealthy, mid-task hijacking attack that successfully compromises browser agents during long-horizon tasks by seamlessly fusing malicious instructions with the original user goal.

The paper introduces SPARROW, an autonomous, open-source platform that uses solar power, edge AI, and satellite communication to enable continuous, scalable biodiversity monitoring in remote global ec…

The paper introduces Terminal Wrench, a comprehensive dataset of 331 reward-hackable terminal-agent environments and 3,632 exploit trajectories, demonstrating that detection of reward hacking degrades…

The paper analyzes a dataset of agent skills, demonstrating that different security scanners (VirusTotal, static analysis, SkillSpector) rarely agree, necessitating a layered governance approach for s…

The paper analyzes a dataset of agent skills, demonstrating that different security scanners (VirusTotal, static analysis, SkillSpector) rarely agree on maliciousness, necessitating layered security g…

The paper analyzes a large sample of AI agent skills, revealing that a significant percentage contain critical security vulnerabilities and malicious payloads, necessitating automated security analysi…

This paper proposes a two-stage method to improve the efficiency and robustness of the Locally Aligned Ant Technique (LAAT) for detecting cosmic structures in noisy, high-dimensional point clouds.

The paper introduces ClawTrap, a MITM-based red-teaming framework, to evaluate the security robustness of web agents like OpenClaw against dynamic, real-world network attacks, finding that model stren…

A lightweight sensor-driven Lévy walk controller is presented for efficient autonomous exploration of minimal-sensing, resource-constrained nano-UAVs.

This paper introduces Test-Time-Training Robot Policies (RoboTTT), a robot model and training recipe that scales visuomotor context to 8K timesteps, enabling new capabilities like one-shot imitation a…

The paper introduces TASTE, an automatic task synthesis method that generates challenging agent benchmarks by evolving tool sequences, demonstrating that existing benchmarks are saturated and that TAS…

This paper addresses the security vulnerabilities in drone swarm control algorithms by proposing two fuzzing tools, SwarmFuzzGraph and SwarmFuzzBinary, to discover Swarm Propagation Vulnerabilities (S…

The paper introduces APIOT, the first LLM framework capable of autonomously performing the full discovery, exploitation, patching, and verification cycle against bare-metal industrial OT devices.