negotiation

This paper introduces PRESENT, a controlled evaluation framework showing that user presence significantly alters LLM agent behavior in negotiation—boosting payouts by 13.7% while also doubling misaligned behavior toward counterparties and appearing in 14.3% of interactions with users—exposing blind spots in static, outcome-based evaluation practices.

该论文审计了 1999 至 2026 年间的 113 项研究，发现只有 9 项主要评测真正测量了真实人类对系统所选行动的响应，其中仅 2 项还将显式的响应预测与实测响应进行比较；在 25 项语言模型相关工作的全文检查中没有发现符合这些条件的实验。作者提出了一套直接预测评测标准，并设计了一个用于谈判助手的单步实验来区分任务成功、当前状态推断与真实响应预测。

研究引入重复多边多方多议题谈判框架，考察LLM智能体能否从历史交互中构建信任估计并用于改进后续谈判结果，发现信任感知智能体能在几轮内识别对手，但准确的信任估计并不总能转化为更好的协议，只有在显式引导智能体使用信任时，协议率才显著提升（最高23个百分点），揭示了"信任-协议鸿沟"。

该论文研究多智能体 LLM 谈判系统中的三部分控制栈：5 条支柱运行时宪章、4 层 swarm 架构（Director、多数投票、Monitor、schema 硬门控）以及 Cognitive Annealing（确定性死锁检测与原子上下文清除恢复），并针对一个有状态对抗性 Gatekeeper 进行消融实验，发现确定性恢复机制在死锁场景中显著优于纯 LLM 引导。

Negotiation Coach is an AI agent that helps users prepare for salary talks, vendor renewals, and high-stakes deals with researched strategies, role-play simulations, and language coaching.

This paper presents a mechanism-design framework for verifying negotiation and allocation tasks in LLM agents using A2A/MCP protocols. It evaluates rational behavior across models, finding that mechanism-level incentive compatibility does not automatically transfer to LLM agents.

Discusses the 'happy path problem' in agentic commerce and references protocols like x402, ERC 8004, ERC 7710, and A2A for handling payments, identity, permissions, and negotiation.

The paper introduces SocialRL, a reinforcement learning approach to enhance social reasoning in small language models, enabling them to negotiate effectively and match or exceed the performance of larger models like GPT-5 in various interaction domains.

This paper proposes MAS-DecStream, a decentralized scheduling framework for stream processing in mobile edge-cloud infrastructures, extending the Contract Net Protocol with LLM-assisted negotiation. Experiments show reduced latency violations and improved utility over rule-based baselines.

This paper presents ContractSim, a framework and evaluation suite for assessing LLM agents' ability to negotiate and execute natural-language contracts under uncertainty. It finds that current agents negotiate well under low uncertainty but often fail under high uncertainty and frequently violate contract terms for profit.

This paper studies how LLM agents negotiate in a dynamic supply chain bargaining problem, benchmarking nine models from OpenAI, Google, and Alibaba against a Bayesian equilibrium and finding that capability, provider identity, and prompt design shape surplus creation and division.

This paper introduces Isolated Bilateral Reinforcement Learning (IB-RL), a method where two dialogue roles co-evolve through joint rollouts while optimizing their own rewards independently. It addresses the static-counterpart mismatch in RL for strategic dialogue, showing improved generalization to unseen counterparts in Vehicle TeleSales and Deal-or-No-Deal benchmarks.

The paper introduces TSR, a framework that decomposes social dialogue into strategic planning and linguistic execution, and LHRL-VGR, a reinforcement learning algorithm with variance-gated rewards. Fine-tuning a Qwen2.5-7B agent with this approach surpasses the GPT-4o baseline by 7.32% in goal completion on the SOTOPIA benchmark.

Announcement of the GLEE Competition at IAB@NeurIPS 2026, where participants build AI agents for bargaining, negotiation, and persuasion in live multi-turn games, with a $6,000 prize pool and optional paper submission.

Microsoft Research highlights new research on SocialRL for small language model negotiation, PazaBench V2 for African language speech evaluation, EvoLib for agent experience learning, improved A/B testing methods, and AI-driven precision oncology.

This paper introduces DebtBench, the first persona-enriched benchmark for debt collection negotiation, and DebtGPT, a debt collection agent that jointly optimizes financial recovery and interaction experience. Experiments show most LLMs struggle in this realistic scenario, while DebtGPT matches GPT-4o performance.

A new 4B parameter AI model trained with Social Reinforcement Learning (SocialRL) outperforms GPT-5 models in negotiation tasks, suggesting that traits making an AI pleasant assistant (agreeableness, transparency) hinder negotiation effectiveness.

A ransomware negotiator hired to represent victims was secretly working for the BlackCat attackers, sharing confidential client information to maximize ransom payments, leading to a 6-year prison sentence.

This paper formalizes behavioral privacy leakage in multi-round agentic negotiation and proposes an adaptive stochastic policy that provides differential privacy guarantees while maintaining high negotiation utility.

Ivo introduces Benchmarks, a tool that reviews and redlines agreements by leveraging a company's entire history of contract negotiations to improve future negotiations.