Copertina

AgenticPay: A Multi-Agent LLM Negotiation System for Buyer-Seller Transactions

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Liu, Xianyang, Gu, Shangding, Song, Dawn
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Long Context, Less Focus: A Scaling Gap in LLMs Revealed through Privacy and Personalization
di: Gu, Shangding
Pubblicazione: (2026)

Understanding Agent Scaling in LLM-Based Multi-Agent Systems via Diversity
di: Yang, Yingxuan, et al.
Pubblicazione: (2026)

Agentic Web: Weaving the Next Web with AI Agents
di: Yang, Yingxuan, et al.
Pubblicazione: (2025)

Data Uniformity Improves Training Efficiency and More, with a Convergence Framework Beyond the NTK Regime
di: Wang, Yuqing, et al.
Pubblicazione: (2025)

Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning
di: Gu, Shangding, et al.
Pubblicazione: (2024)

MemFail: Stress-Testing Failure Modes of LLM Memory Systems
di: Garg, Ishir, et al.
Pubblicazione: (2026)

Paying Less Generalization Tax: A Cross-Domain Generalization Study of RL Training for LLM Agents
di: Liu, Zhihan, et al.
Pubblicazione: (2026)

What Makes a Sale? Rethinking End-to-End Seller--Buyer Retail Dynamics with LLM Agents
di: Choi, Jeonghwan, et al.
Pubblicazione: (2026)

When Do Multi-Agent Systems Outperform? Analysing the Learning Efficiency of Agentic Systems
di: Su, Junwei, et al.
Pubblicazione: (2026)

AgentFlux: Decoupled Fine-Tuning & Inference for On-Device Agentic Systems
di: Kadekodi, Rohan, et al.
Pubblicazione: (2025)

A Review of Safe Reinforcement Learning: Methods, Theory and Applications
di: Gu, Shangding, et al.
Pubblicazione: (2022)

Agentic Unlearning: When LLM Agent Meets Machine Unlearning
di: Wang, Bin, et al.
Pubblicazione: (2026)

Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation
di: Gu, Shangding, et al.
Pubblicazione: (2024)

LLMs Should Express Uncertainty Explicitly
di: Guo, Junyu, et al.
Pubblicazione: (2026)

StyleBench: Evaluating thinking styles in Large Language Models
di: Guo, Junyu, et al.
Pubblicazione: (2025)

LeakAgent: RL-based Red-teaming Agent for LLM Privacy Leakage
di: Nie, Yuzhou, et al.
Pubblicazione: (2024)

Hybrid Agentic AI and Multi-Agent Systems in Smart Manufacturing
di: Farahani, Mojtaba A., et al.
Pubblicazione: (2025)

[Re] Benchmarking LLM Capabilities in Negotiation through Scoreable Games
di: Pollo, Jorge Carrasco, et al.
Pubblicazione: (2026)

A Benchmark for Multi-Party Negotiation Games from Real Negotiation Data
di: Benac, Leo, et al.
Pubblicazione: (2026)

ARM: Discovering Agentic Reasoning Modules for Generalizable Multi-Agent Systems
di: Yao, Bohan, et al.
Pubblicazione: (2025)

Multi-Agent Debate: A Unified Agentic Framework for Tabular Anomaly Detection
di: Wang, Pinqiao, et al.
Pubblicazione: (2026)

What Limits Agentic Systems Efficiency?
di: Bian, Song, et al.
Pubblicazione: (2025)

Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems
di: Feng, Lang, et al.
Pubblicazione: (2026)

On the Importance of Task Complexity in Evaluating LLM-Based Multi-Agent Systems
di: Tang, Bohan, et al.
Pubblicazione: (2025)

Safe Multi-Agent Reinforcement Learning with Bilevel Optimization in Autonomous Driving
di: Zheng, Zhi, et al.
Pubblicazione: (2024)

Multi-View Encoders for Performance Prediction in LLM-Based Agentic Workflows
di: Trirat, Patara, et al.
Pubblicazione: (2025)

When Reasoning Models Hurt Behavioral Simulation: A Solver-Sampler Mismatch in Multi-Agent LLM Negotiation
di: Andric, Sandro
Pubblicazione: (2026)

GoAgent: Group-of-Agents Communication Topology Generation for LLM-based Multi-Agent Systems
di: Chen, Hongjiang, et al.
Pubblicazione: (2026)

Scaling Graph Chain-of-Thought Reasoning: A Multi-Agent Framework with Efficient LLM Serving
di: Huan, Chengying, et al.
Pubblicazione: (2025)

GSM-Agent: Understanding Agentic Reasoning Using Controllable Environments
di: Zhu, Hanlin, et al.
Pubblicazione: (2025)

Fed-SE: Federated Self-Evolution for Privacy-Constrained Multi-Environment LLM Agents
di: Chen, Xiang, et al.
Pubblicazione: (2025)

Contextual Dynamic Pricing with Strategic Buyers
di: Liu, Pangpang, et al.
Pubblicazione: (2023)

Harnessing Agentic Evolution
di: Zhang, Jiayi, et al.
Pubblicazione: (2026)

Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning
di: Gu, Shangding, et al.
Pubblicazione: (2025)

dLLM: Simple Diffusion Language Modeling
di: Zhou, Zhanhui, et al.
Pubblicazione: (2026)

Agentic Neural Networks: Self-Evolving Multi-Agent Systems via Textual Backpropagation
di: Ma, Xiaowen, et al.
Pubblicazione: (2025)

Reliable Self-Harm Risk Screening via Adaptive Multi-Agent LLM Systems
di: Karnam, Meghana, et al.
Pubblicazione: (2026)

MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
di: Wang, Zhexuan, et al.
Pubblicazione: (2026)

Temporal-Aware Graph Attention Network for Cryptocurrency Transaction Fraud Detection
di: Zheng, Zhi, et al.
Pubblicazione: (2025)

Act Only When It Pays: Efficient Reinforcement Learning for LLM Reasoning via Selective Rollouts
di: Zheng, Haizhong, et al.
Pubblicazione: (2025)