LLM Agents Making Agent Tools
Fuente:
arXiv
Guardado en:
| Autores principales: | Wölflein, Georg, Ferber, Dyke, Truhn, Daniel, Arandjelović, Ognjen, Kather, Jakob Nikolas |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
TrustAgent: Towards Safe and Trustworthy LLM-based Agents
por: Hua, Wenyue, et al.
Publicado: (2024)
por: Hua, Wenyue, et al.
Publicado: (2024)
Opponent Shaping in LLM Agents
por: Segura, Marta Emili Garcia, et al.
Publicado: (2025)
por: Segura, Marta Emili Garcia, et al.
Publicado: (2025)
Dive into the Agent Matrix: A Realistic Evaluation of Self-Replication Risk in LLM Agents
por: Zhang, Boxuan, et al.
Publicado: (2025)
por: Zhang, Boxuan, et al.
Publicado: (2025)
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
por: Trirat, Patara, et al.
Publicado: (2024)
por: Trirat, Patara, et al.
Publicado: (2024)
$\textit{Agents Under Siege}$: Breaking Pragmatic Multi-Agent LLM Systems with Optimized Prompt Attacks
por: Khan, Rana Muhammad Shahroz, et al.
Publicado: (2025)
por: Khan, Rana Muhammad Shahroz, et al.
Publicado: (2025)
Can Agents Judge Systematic Reviews Like Humans? Evaluating SLRs with LLM-based Multi-Agent System
por: Mushtaq, Abdullah, et al.
Publicado: (2025)
por: Mushtaq, Abdullah, et al.
Publicado: (2025)
An Adversary-Resistant Multi-Agent LLM System via Credibility Scoring
por: Ebrahimi, Sana, et al.
Publicado: (2025)
por: Ebrahimi, Sana, et al.
Publicado: (2025)
MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
por: Wang, Zhexuan, et al.
Publicado: (2026)
por: Wang, Zhexuan, et al.
Publicado: (2026)
SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories
por: Yu, Zhuoyun, et al.
Publicado: (2026)
por: Yu, Zhuoyun, et al.
Publicado: (2026)
Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control
por: Rezazadeh, Alireza, et al.
Publicado: (2025)
por: Rezazadeh, Alireza, et al.
Publicado: (2025)
RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation
por: Shen, Chengzhi, et al.
Publicado: (2026)
por: Shen, Chengzhi, et al.
Publicado: (2026)
GAMBIT: A Three-Mode Benchmark for Adversarial Robustness in Multi-Agent LLM Collectives
por: Mercier, Alexandre Le, et al.
Publicado: (2026)
por: Mercier, Alexandre Le, et al.
Publicado: (2026)
Towards Reliable ML Feature Engineering via Planning in Constrained-Topology of LLM Agents
por: Thakur, Himanshu, et al.
Publicado: (2026)
por: Thakur, Himanshu, et al.
Publicado: (2026)
Multi-Agent Design: Optimizing Agents with Better Prompts and Topologies
por: Zhou, Han, et al.
Publicado: (2025)
por: Zhou, Han, et al.
Publicado: (2025)
Recursive Agent Optimization
por: Gandhi, Apurva, et al.
Publicado: (2026)
por: Gandhi, Apurva, et al.
Publicado: (2026)
SPIO: Ensemble and Selective Strategies via LLM-Based Multi-Agent Planning in Automated Data Science
por: Seo, Wonduk, et al.
Publicado: (2025)
por: Seo, Wonduk, et al.
Publicado: (2025)
AgentRec: Agent Recommendation Using Sentence Embeddings Aligned to Human Feedback
por: Park, Joshua, et al.
Publicado: (2025)
por: Park, Joshua, et al.
Publicado: (2025)
DR. WELL: Dynamic Reasoning and Learning with Symbolic World Model for Embodied LLM-Based Multi-Agent Collaboration
por: Nourzad, Narjes, et al.
Publicado: (2025)
por: Nourzad, Narjes, et al.
Publicado: (2025)
Towards Efficient LLM Grounding for Embodied Multi-Agent Collaboration
por: Zhang, Yang, et al.
Publicado: (2024)
por: Zhang, Yang, et al.
Publicado: (2024)
Language Agents as Optimizable Graphs
por: Zhuge, Mingchen, et al.
Publicado: (2024)
por: Zhuge, Mingchen, et al.
Publicado: (2024)
MedAgentBoard: Benchmarking Multi-Agent Collaboration with Conventional Methods for Diverse Medical Tasks
por: Zhu, Yinghao, et al.
Publicado: (2025)
por: Zhu, Yinghao, et al.
Publicado: (2025)
KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents
por: Zhu, Yuqi, et al.
Publicado: (2024)
por: Zhu, Yuqi, et al.
Publicado: (2024)
LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions
por: Sun, Chuanneng, et al.
Publicado: (2024)
por: Sun, Chuanneng, et al.
Publicado: (2024)
Memp: Exploring Agent Procedural Memory
por: Fang, Runnan, et al.
Publicado: (2025)
por: Fang, Runnan, et al.
Publicado: (2025)
Agent Trading Arena: A Study on Numerical Understanding in LLM-Based Agents
por: Ma, Tianmi, et al.
Publicado: (2025)
por: Ma, Tianmi, et al.
Publicado: (2025)
MAC: Multi-Agent Constitution Learning
por: Thareja, Rushil, et al.
Publicado: (2026)
por: Thareja, Rushil, et al.
Publicado: (2026)
Verification-Aware Planning for Multi-Agent Systems
por: Xu, Tianyang, et al.
Publicado: (2025)
por: Xu, Tianyang, et al.
Publicado: (2025)
Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View
por: Zhang, Jintian, et al.
Publicado: (2023)
por: Zhang, Jintian, et al.
Publicado: (2023)
Toward Super Agent System with Hybrid AI Routers
por: Yao, Yuhang, et al.
Publicado: (2025)
por: Yao, Yuhang, et al.
Publicado: (2025)
MARCO: Multi-Agent Real-time Chat Orchestration
por: Shrimal, Anubhav, et al.
Publicado: (2024)
por: Shrimal, Anubhav, et al.
Publicado: (2024)
Context, Reasoning, and Hierarchy: A Cost-Performance Study of Compound LLM Agent Design in an Adversarial POMDP
por: Bogdanov, Igor, et al.
Publicado: (2026)
por: Bogdanov, Igor, et al.
Publicado: (2026)
Can We Predict Before Executing Machine Learning Agents?
por: Zheng, Jingsheng, et al.
Publicado: (2026)
por: Zheng, Jingsheng, et al.
Publicado: (2026)
Training Language Models for Social Deduction with Multi-Agent Reinforcement Learning
por: Sarkar, Bidipta, et al.
Publicado: (2025)
por: Sarkar, Bidipta, et al.
Publicado: (2025)
PAACE: A Plan-Aware Automated Agent Context Engineering Framework
por: Yuksel, Kamer Ali
Publicado: (2025)
por: Yuksel, Kamer Ali
Publicado: (2025)
Unleashing Diverse Thinking Modes in LLMs through Multi-Agent Collaboration
por: He, Zhixuan, et al.
Publicado: (2025)
por: He, Zhixuan, et al.
Publicado: (2025)
Symphony: A Decentralized Multi-Agent Framework for Scalable Collective Intelligence
por: Wang, Ji, et al.
Publicado: (2025)
por: Wang, Ji, et al.
Publicado: (2025)
Multi-Agent Constraint Factorization Reveals Latent Invariant Solution Structure
por: Scofield, Christopher
Publicado: (2026)
por: Scofield, Christopher
Publicado: (2026)
ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning
por: Wan, Ziyu, et al.
Publicado: (2025)
por: Wan, Ziyu, et al.
Publicado: (2025)
MLZero: A Multi-Agent System for End-to-end Machine Learning Automation
por: Fang, Haoyang, et al.
Publicado: (2025)
por: Fang, Haoyang, et al.
Publicado: (2025)
Doctorina MedBench: End-to-End Evaluation of Agent-Based Medical AI
por: Kozlova, Anna, et al.
Publicado: (2026)
por: Kozlova, Anna, et al.
Publicado: (2026)
Ejemplares similares
-
TrustAgent: Towards Safe and Trustworthy LLM-based Agents
por: Hua, Wenyue, et al.
Publicado: (2024) -
Opponent Shaping in LLM Agents
por: Segura, Marta Emili Garcia, et al.
Publicado: (2025) -
Dive into the Agent Matrix: A Realistic Evaluation of Self-Replication Risk in LLM Agents
por: Zhang, Boxuan, et al.
Publicado: (2025) -
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
por: Trirat, Patara, et al.
Publicado: (2024) -
$\textit{Agents Under Siege}$: Breaking Pragmatic Multi-Agent LLM Systems with Optimized Prompt Attacks
por: Khan, Rana Muhammad Shahroz, et al.
Publicado: (2025)