mlsanityData to 7 Oct 2026

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

arXiv 2602.06008 ↗First posted 5 Feb 2026cs.AI cs.LGcited by 11

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

Large language model (LLM)-based agents are increasingly expected to negotiate, coordinate, and transact autonomously, yet existing benchmarks lack principled settings for evaluating language-mediated economic interaction among multiple agents. We introduce AgenticPay, a benchmark and simulation framework for multi-agent buyer-seller negotiation driven by natural language. AgenticPay models markets in which buyers and sellers possess private constraints and product-dependent valuations, and must reach agreements through multi-round linguistic negotiation rather than numeric bidding alone. The framework supports a diverse suite of over 110 tasks ranging from bilateral bargaining to many-to-many markets, with structured action extraction and metrics for feasibility, efficiency, and welfare. Benchmarking state-of-the-art proprietary and open-weight LLMs reveals substantial gaps in negotiation performance and highlights challenges in long-horizon strategic reasoning, establishing AgenticPay as a foundation for studying agentic commerce and language-based market interaction. Code and dataset are available at the link: https://github.com/SafeRL-Lab/AgenticPay.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 28 of its 47 references that are in the map. First posted on arXiv 5 Feb 2026.

Builds on

28 of 47 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025Evaluating LLM Agent Collusion in Double Auctions2 Jul
  2. 2025HARBOR: Exploring Persona Dynamics in Multi-Agent Competition17 Feb
  3. 2023Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arena9 Oct

Other references · 25

  1. 2024GPT-4o System Cardcited by 4,467
  2. 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,655
  3. 2024Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Modelscited by 552
  4. 2023Playing repeated games with Large Language Modelscited by 213
  5. 2017Deal or No Deal? End-to-End Learning for Negotiation Dialoguescited by 202
  6. 2023Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedbackcited by 202
  7. 2018Decoupling Strategy and Generation in Negotiation Dialoguescited by 156
  8. 2024A Survey on Large Language Model-Based Game Agentscited by 106
  9. 2024How Well Can LLMs Negotiate? NegotiationArena Platform and Analysiscited by 93
  10. 2023Can Large Language Models Serve as Rational Players in Game Theory? A Systematic Analysiscited by 91
  11. 2024Beyond Accuracy: Evaluating the Reasoning Behavior of Large Language Models -- A Surveycited by 82
  12. 2021CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systemscited by 60
13 more
  1. 2023Strategic Behavior of Large Language Models: Game Structure vs. Contextual Framingcited by 49
  2. 2024Measuring Bargaining Abilities of LLMs: A Benchmark and A Buyer-Enhancement Methodcited by 44
  3. 2025Agentic Web: Weaving the Next Web with AI Agentscited by 43
  4. 2024STEER: Assessing the Economic Rationality of Large Language Modelscited by 26
  5. 2021DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialoguescited by 25
  6. 2025Preference-Aware Memory Update for Long-Term LLM Agentscited by 19
  7. 2024Assistive Large Language Model Agents for Socially-Aware Negotiation Dialoguescited by 18
  8. 2025LLM Strategic Reasoning: Agentic Study through Behavioral Game Theorycited by 14
  9. 2025LLM Bidders Preserve the Mechanism-Level Orderings of Human Bidderscited by 10
  10. 2024Large Language Models Playing Mixed Strategy Nash Equilibrium Gamescited by 9
  11. 2025AccidentBench: Benchmarking Multimodal Understanding and Reasoning in Vehicle Accidents and Beyondcited by 8
  12. 2024TeaMs-RL: Teaching LLMs to Generate Better Instruction Datasets via Reinforcement Learningcited by 4
  13. 2024Using Large Language Models for Humanitarian Frontline Negotiation: Opportunities and Considerationscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 11.

11 papers.

  1. 2026SoK: Security of Autonomous LLM Agents in Agentic Commercecited by 8
  2. 2026From Model Scaling to System Scaling: Scaling the Harness in Agentic AIcited by 8
  3. 2026TERMS-Bench: Diagnosing LLM Negotiation Agents Beyond Deal Ratecited by 6
  4. 2026Organizational Control Layer: Governance Infrastructure at the Execution Boundary of LLM Agent Systemscited by 3
  5. 2026Commitment To Cooperation With Self-Negotiated Contractscited by 1
  6. 2026Agentic Commerce World: An Auditable and Verifiable Environment for Vibe Commercecited by 1
  7. 2026Counterparty Modeling is Not Strategy: The Limits of LLM Negotiatorscited by 0
  8. 2026Paying to Know: Micro-Transaction Markets for Verified Product Information in Agentic E-Commercecited by 0
  9. 2026CoWeaver: A Bi-directional, Learnable and Explainable Matching Engine for Mixed Human-Agent Science Collaborationcited by 0
  10. 2026Evaluating Rational Contracting in Natural Languagecited by 0
  11. 2026From Process Loss to Assembly Bonus: Human-Grounded Diagnosis of Multi-Agent LLM Collaborationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Learning to Sell: Reinforcement Learning for Strategic Large Language Model Agents in Multi-Product Markets
  2. 2024AgreeMate: Teaching LLMs to Haggle
  3. 2026Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition
  4. 2025Evaluating Multi-Turn Bargain Skills in LLM-Based Seller Agent
  5. 2026E-Commerce Bench: Evaluating LLM Agents on Long-Horizon Autonomous Business Operation
  6. 2026Competitive Market Behavior of LLMs
  7. 2026Agentic Trading: When LLM Agents Meet Financial Markets
  8. 2025LLM-based Multi-Agent System for Simulating Strategic and Goal-Oriented Data Marketplaces