# CREFT: Sequential Multi-Agent LLM for Character Relation Extraction

arXiv: https://arxiv.org/abs/2505.24553 · HTML: https://mlsanity.com/paper/2505.24553/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use.
- Builds on 3 of its 19 references that are in the map.
- First posted on arXiv 30 May 2025.

## Placed in

- LLM agents and tool use / [Multimodal and embodied agents](https://mlsanity.com/agents/multimodal-and-embodied-agents/)

## Builds on (most cited first, 3 of 3)

- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [Large Language Models Fall Short: Understanding Complex Relationships in Detective Narratives](https://mlsanity.com/paper/2402.11051/) (2024)
- [Agent-as-Judge for Factual Summarization of Long Narratives](https://mlsanity.com/paper/2501.09993/) (2025)

## Built on by (most cited first, 2 of 2)

- [Overcoming Copyright Barriers in Corpus Distribution Through Non-Reversible Hashing](https://mlsanity.com/paper/2604.23412/) (2026)
- [MechReason: Benchmarking Multi-Image Multi-Hop Reasoning in Mechanical Engineering](https://mlsanity.com/paper/2609.16012/) (2026)

## Abstract (arXiv)

Understanding complex character relations is crucial for narrative analysis and efficient script evaluation, yet existing extraction methods often fail to handle long-form narratives with nuanced interactions. To address this challenge, we present CREFT, a novel sequential framework leveraging specialized Large Language Model (LLM) agents. First, CREFT builds a base character graph through knowledge distillation, then iteratively refines character composition, relation extraction, role identification, and group assignments. Experiments on a curated Korean drama dataset demonstrate that CREFT significantly outperforms single-agent LLM baselines in both accuracy and completeness. By systematically visualizing character networks, CREFT streamlines narrative comprehension and accelerates script review -- offering substantial benefits to the entertainment, publishing, and educational sectors.