← Search

Shinnosuke Hirano

2 accepted papers

2026

LLM-Free Image Captioning Evaluation in Reference-Flexible Settings

AAAI 2026technical

We focus on the automatic evaluation of image captions in both reference-based and reference-free settings. Existing metrics based on large language models (LLMs) favor their own generations; therefore, the neutrality is in question. Most LLM-free metrics do not suffer from such an issue, whereas th

Cited by 0SourcePDFScholar
2025

VELA: An LLM-Hybrid-as-a-Judge Approach for Evaluating Long Image Captions

EMNLP 2025

In this study, we focus on the automatic evaluation of long and detailed image captions generated by multimodal Large Language Models (MLLMs). Most existing automatic evaluation metrics for image captioning are primarily designed for short captions and are not suitable for evaluating long captions.

Cited by 0SourcePDFScholar