# Automated Analysis Framework for Multilingual Climate-Health Literature Based on Multi-Agent Large Language Model

arXiv: https://arxiv.org/abs/2608.27998 · HTML: https://mlsanity.com/paper/2608.27998/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 34 references that are in the map.
- First posted on arXiv 28 Aug 2026.

## Builds on (most cited first, 13 of 13)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation](https://mlsanity.com/paper/2308.08155/) (2023)
- [Evaluating Large Language Models at Evaluating Instruction Following](https://mlsanity.com/paper/2310.07641/) (2023)
- [Scaling Large Language Model-based Multi-Agent Collaboration](https://mlsanity.com/paper/2406.07155/) (2024)
- [Large Language Models for Generative Information Extraction: A Survey](https://mlsanity.com/paper/2312.17617/) (2023)
- [OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts](https://mlsanity.com/paper/2205.01833/) (2022)
- [Extracting Accurate Materials Data from Research Papers with Conversational Language Models and Prompt Engineering](https://mlsanity.com/paper/2303.05352/) (2023)
- [LiRA: A Multi-Agent Framework for Reliable and Readable Literature Review Generation](https://mlsanity.com/paper/2510.05138/) (2025)
- [Science Across Languages: Assessing LLM Multilingual Translation of Scientific Papers](https://mlsanity.com/paper/2502.17882/) (2025)
- [DITING: A Multi-Agent Evaluation Framework for Benchmarking Web Novel Translation](https://mlsanity.com/paper/2510.09116/) (2025)
- [ResearchPilot: A Local-First Multi-Agent System for Literature Synthesis and Related Work Drafting](https://mlsanity.com/paper/2603.14629/) (2026)
- [Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework](https://mlsanity.com/paper/2604.06170/) (2026)
- [An Explainable Approach to Document-level Translation Evaluation with Topic Modeling](https://mlsanity.com/paper/2604.20334/) (2026)

## Abstract (arXiv)

The rapid proliferation of interdisciplinary and multilingual scientific literature has left traditional manual analysis and single-algorithm methods plagued by low efficiency, poor scalability, and insufficient domain adaptability. Targeting the literature analysis needs of the typical interdisciplinary climate-health field, this study proposes a multi-agent large language model automated analysis framework for multilingual scientific literature, which realizes full-process automation covering literature screening, structured information extraction, and standardized integration. With a central coordination module as the core, the framework deploys three dedicated agents for document evaluation, information extraction, and analytical review to mimic the literature analysis thinking of domain experts, and adopts a four-layer hallucination control strategy together with a manual verification procedure to ensure the accuracy and reliability of analytical outcomes. Validated on a bilingual Chinese-English corpus of 32,642 climate-health papers covering China from 1993 to 2023, the framework achieves an F1 score of 0.92 in core information extraction, and completes the extraction and standardization of 2,012 city-literature association pairs, offering effective technical support for large-scale evidence mining in the climate-health research domain.