PulseAugur
LIVE 16:11:05
research · [3 sources] ·
0
research

New BOND framework uses distilled LLMs for auditable negotiation

By PulseAugur Editorial · Summary by gemini-2.5-flash-lite from 3 sources

Researchers have developed a new framework called BOND (Bayesian Opponent-belief Negotiation Distillation) to make negotiation agents more auditable. This system uses a large language model to infer and update beliefs about an opponent's values during dialogue. A smaller, distilled model then uses these beliefs to make decisions and can output normalized posterior beliefs, outperforming existing state-of-the-art methods on the CaSiNo negotiation dataset. AI

Summary written by gemini-2.5-flash-lite from 3 sources. How we write summaries →

IMPACT Introduces a method for making LLM-based negotiation agents more transparent and auditable.

RANK_REASON This is a research paper detailing a new framework for AI negotiation agents.

Read on arXiv cs.CL →

COVERAGE [3]

  1. arXiv cs.CL TIER_1 · Zongqi Cui, Baihan Lin ·

    Distilling Bayesian Belief States into Language Models for Auditable Negotiation

    arXiv:2605.04507v1 Announce Type: new Abstract: Negotiation agents must infer what their counterpart values, update those beliefs over dialogue turns, and choose actions under uncertainty. End-to-end large language models (LLMs) can imitate negotiation dialogue, but their opponen…

  2. arXiv cs.CL TIER_1 · Baihan Lin ·

    Distilling Bayesian Belief States into Language Models for Auditable Negotiation

    Negotiation agents must infer what their counterpart values, update those beliefs over dialogue turns, and choose actions under uncertainty. End-to-end large language models (LLMs) can imitate negotiation dialogue, but their opponent beliefs are usually implicit and difficult to …

  3. Hugging Face Daily Papers TIER_1 ·

    Distilling Bayesian Belief States into Language Models for Auditable Negotiation

    Negotiation agents must infer what their counterpart values, update those beliefs over dialogue turns, and choose actions under uncertainty. End-to-end large language models (LLMs) can imitate negotiation dialogue, but their opponent beliefs are usually implicit and difficult to …

RELATED ENTITIES

RELATED TOPICS