Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
arXiv:2610.34238v1 Announce Type: cross Abstract: In this paper, we introduce $\Delta\tau$-Bench, an executable agent benchmark that models the structural evolution of large tool ecosystems. In $\Del...
arXiv:2610.34450v1 Announce Type: cross Abstract: Decentralized multi-agent systems (MAS) enable large language model agents to interact without centralized control. Agents need to adapt to other age...
arXiv:2610.34542v1 Announce Type: cross Abstract: Autonomous agents have been observed acting beyond their assigned tasks, accessing unauthorized systems, and establishing communication channels to e...
arXiv:2610.34649v1 Announce Type: cross Abstract: Recent advances in vision-language-action (VLA) and world-action models (WAMs) have significantly improved robotic manipulation, yet deploying robots...
arXiv:2610.34763v1 Announce Type: cross Abstract: Coding agents resend a growing context on every model call, and context policies are usually judged by the prompt tokens they save. Executed work als...
arXiv:2610.34965v1 Announce Type: cross Abstract: Automatic red teaming increasingly relies on large language models (LLMs) to iteratively diagnose failed attacks and propose improved adversarial pro...
arXiv:2610.35082v1 Announce Type: cross Abstract: Agent Skills allow LLM agents to combine reusable capabilities, but checking each Skill in isolation cannot rule out policy violations when they are...
arXiv:2610.35188v1 Announce Type: cross Abstract: Large language models increasingly act through code, modifying repositories, executing programs, and interacting with services in agent form. Their a...
arXiv:2610.35240v1 Announce Type: cross Abstract: India's historical public archives present severe computer vision and document image analysis challenges: decades of parliamentary records survive on...
arXiv:2610.35333v1 Announce Type: cross Abstract: Code agents have become increasingly capable of performing software engineering tasks through interaction with software environments. However, agents...
arXiv:2610.35829v1 Announce Type: cross Abstract: A vulnerability costs more to fix the later it is discovered. As coding agents generate code faster than developers can review it, software needs a f...
arXiv:2601.06640v2 Announce Type: replace Abstract: The transition towards sixth-generation (6G) wireless networks necessitates autonomous orchestration mechanisms capable of translating high-level o...
arXiv:2605.17746v2 Announce Type: replace Abstract: Human-AI experiments vary who receives information, who can act, and who holds decision authority. Precise descriptions of individual studies do no...
arXiv:2608.26036v2 Announce Type: replace Abstract: Large language model (LLM) data agents answer structured-data questions by generating SQL, invoking tools, executing queries, and summarizing resul...
arXiv:2609.33357v2 Announce Type: replace Abstract: Reliable automated research requires agents to vet data, verify analyses, and generate hypotheses grounded in trustworthy evidence, potentially red...
arXiv:2609.35501v2 Announce Type: replace Abstract: Recent agentic symbolic regression approaches increasingly rely on large language models to analyze data, select scientific operations, and refine...
arXiv:2610.31372v2 Announce Type: replace Abstract: Autonomous research agents are increasingly used to automate large portions of scientific research, yet they are prone to research integrity violat...
arXiv:2610.27293v2 Announce Type: replace Abstract: Safe Multi-Agent Reinforcement Learning (SMARL) aims to learn cooperative control policies under prescribed safety constraints. Al- though existing...
arXiv:2602.08054v2 Announce Type: replace-cross Abstract: Offline reinforcement learning (RL) offers a promising framework for deploying autonomous systems in safety-critical settings without the ris...
arXiv:2605.06908v2 Announce Type: replace-cross Abstract: Adaptive test-time compute for LLM agents aims to invoke extra computation only when it improves performance. Existing methods typically use...