arXiv AI
Aug 11
What Keeps Agent Skills from Being Reusable? Evidence from 138K SKILL.md Files
arXiv:2608. 08453v1 Announce Type: new Abstract: Under the current standard, Agent Skills are SKILL.
AI agents
Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
arXiv AI
Aug 11
Branch2Skill: Efficient Skill Evolution Through Reasoning Trees
arXiv:2608. 08677v1 Announce Type: new Abstract: Skill evolution improves agent skills through feedback over time, with failed trajectories often providing informative signals by revealing incomplete or misleading behaviors.
arXiv AI
Aug 11
EnergyBridge: Benchmarking Household Energy Management, User Participation, and Grid Flexibility
arXiv:2608. 08691v1 Announce Type: new Abstract: Residential virtual power plants (VPPs) can provide grid flexibility by shifting household demand, but physical flexibility becomes dependable capacity only when residents authorize a plan and the promised response is delivered.
arXiv AI
Aug 11
MARA: Flow-Matching-Guided Multi-Agent Resource Allocation for Computational Resource Efficient Learning
arXiv:2608. 09130v1 Announce Type: cross Abstract: Allocating limited computation among concurrent learning tasks is difficult when each task must reach a target loss before a deadline but its required training effort is unknown.
arXiv Machine Learning
Aug 11
Unsupervised Point Cloud Registration with Self-Distillation
arXiv:2409. 07558v2 Announce Type: replace-cross Abstract: Rigid point cloud registration is a fundamental problem and highly relevant in robotics and autonomous driving.
arXiv AI
Aug 11
Private Etymology: Designing Relational Reuse of Shared Symbols in Long-Term Human-AI Interaction
arXiv:2608. 08443v1 Announce Type: cross Abstract: Previous studies have shown that people can develop shared symbols, partner-specific expressions, personal idioms, inside jokes, and other parts of a relational microculture.
arXiv Machine Learning
Aug 11
Preference Redirection via Attention Concentration: An Attack on Computer Use Agents
arXiv:2604. 08005v2 Announce Type: replace Abstract: Advancements in multimodal foundation models have enabled the development of Computer Use Agents (CUAs) capable of autonomously interacting with GUI environments.
arXiv AI
Aug 11
NeuroRefiner: Morphology-Aware Multi-Agent Refinement for 3D Fluorescence Microscopy Neuron Segmentation
arXiv:2608. 09636v1 Announce Type: cross Abstract: Accurate 3D neuron segmentation in fluorescence microscopy is critical for neuroscience.
arXiv AI
Aug 11
In-Situ Behavioral Evaluation for LLM Fairness, Not Standardized-Test Scores
arXiv:2605. 12530v2 Announce Type: replace-cross Abstract: LLM fairness should be evaluated through in-situ behavioral pattern rather than standardized-test Q&A benchmarks.
arXiv AI
Aug 11
CRUISE: Vision-Language Model-Guided Uncertainty-Aware Cross-Modal Sensor Fusion for Robust Autonomous Driving
arXiv:2608. 09202v1 Announce Type: new Abstract: Modern autonomous vehicles are equipped with multiple sensors, such as cameras, LiDAR, and radar, for comprehensive environmental perception.
arXiv AI
Aug 11
Artificial Leviathan: Exploring Social Evolution of LLM Agents Through the Lens of Hobbesian Social Contract Theory
arXiv:2406. 14373v3 Announce Type: replace Abstract: The emergence of Large Language Models (LLMs) and advancements in Artificial Intelligence (AI) offer an opportunity for computational social science research at scale.
arXiv AI
Aug 11
STAIR: Effective Incident Response Using an End-to-End Agentic Planning Framework
arXiv:2608. 09524v1 Announce Type: cross Abstract: Incident response planning is critical for restoring compromised software systems after cyberattacks.
arXiv AI
Aug 11
PluginEval: A Diagnostic Benchmark for Fine-Grained Error Attribution in Function Calling
arXiv:2608. 08700v1 Announce Type: new Abstract: Reliable evaluation of tool routing is critical as Large Language Models increasingly operate as autonomous agents.
arXiv AI
Aug 11
Defining Decentralization: An Ontological Perspective
arXiv:2608. 09748v1 Announce Type: cross Abstract: Decentralization as a concept in computer science has existed for over half a century.
arXiv AI
Aug 11
$A^2E$ : An End-to-End Agent Auditing Engine
arXiv:2608. 07346v2 Announce Type: replace Abstract: With the rapid advancement of large language models (LLMs), harnesses have become essential infrastructure for deploying agents across a wide range of domains.
arXiv Machine Learning
Aug 11
Multi-Agent Reinforcement Learning via Agent-Specific Preference
arXiv:2608. 08604v1 Announce Type: new Abstract: Multi-agent reinforcement learning (MARL) is a powerful framework for solving complex collaborative tasks, but it relies heavily on well-defined global reward functions.
arXiv AI
Aug 11
ActBench: Self-Evolving Benchmark of Behavioral Safety in Cowork Agents
arXiv:2608. 09476v1 Announce Type: cross Abstract: Cowork agents may complete benign tasks while disclosing protected data, manipulating unauthorized state, invocate unauthorized API.
arXiv AI
Aug 11
ToolUniverse: An open platform for democratizing AI scientists
arXiv:2509. 23426v3 Announce Type: replace Abstract: AI scientists are emerging computational systems that serve as collaborative partners in discovery.
arXiv Machine Learning
Aug 11
Distilling Vision-Language Models for Robust Traffic Sign Perception in Autonomous Vehicles
arXiv:2608. 08815v1 Announce Type: new Abstract: Traffic sign recognition (TSR) models based on deep neural networks achieve strong clean-data performance but remain vulnerable to physically realizable adversarial attacks, including shadow perturbations, natural-light interference, and printed patches.
arXiv AI
Aug 11
An AI Scientist that Doesn't Drift: Taste, Structure, and Falsifiable Findings in a Quadruped Navigation Research Loop
arXiv:2608. 07542v1 Announce Type: new Abstract: Autonomous research loops driven by large language models can run machine-learning experiments at scale but tend to drift toward local refinements of whichever metric they optimise rather than testing the hypotheses that motivate the experiments.