all AI news
Modelling Political Coalition Negotiations Using LLM-based Agents
Feb. 20, 2024, 5:51 a.m. | Farhad Moghimifar, Yuan-Fang Li, Robert Thomson, Gholamreza Haffari
cs.CL updates on arXiv.org arxiv.org
Abstract: Coalition negotiations are a cornerstone of parliamentary democracies, characterised by complex interactions and strategic communications among political parties. Despite its significance, the modelling of these negotiations has remained unexplored with the domain of Natural Language Processing (NLP), mostly due to lack of proper data. In this paper, we introduce coalition negotiations as a novel NLP task, and model it as a negotiation between large language model-based agents. We introduce a multilingual dataset, POLCA, comprising manifestos …
abstract agents arxiv coalition communications cs.cl data domain interactions language language processing llm modelling natural natural language natural language processing negotiations nlp paper parties political processing significance type
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
C003549 Data Analyst (NS) - MON 13 May
@ EMW, Inc. | Braine-l'Alleud, Wallonia, Belgium
Marketing Decision Scientist
@ Meta | Menlo Park, CA | New York City