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20232026
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cs.CV2025

LLM-Free Image Captioning Evaluation in Reference-Flexible Settings

Shinnosuke Hirano, Yuiga Wada, Kazuki Matsuda +2

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 g…

cs.CV2025

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

Kazuki Matsuda, Yuiga Wada, Shinnosuke Hirano +2

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 me…

cs.CV2025

Attention Lattice Adapter: Visual Explanation Generation for Visual Foundation Model

Shinnosuke Hirano, Yuiga Wada, Tsumugi Iida +1

In this study, we consider the problem of generating visual explanations in visual foundation models. Numerous methods have been proposed for this purpose; however, they often cann…

cs.CV2025

Capturing Fine-Grained Alignments Improves 3D Affordance Detection

Junsei Tokumitsu, Yuiga Wada

In this work, we address the challenge of affordance detection in 3D point clouds, a task that requires effectively capturing fine-grained alignments between point clouds and text.…

cs.CV2025

ZINA: Multimodal Fine-grained Hallucination Detection and Editing

Yuiga Wada, Kazuki Matsuda, Komei Sugiura +1

Multimodal Large Language Models (MLLMs) often generate hallucinations, where the output deviates from the visual content. Given that these hallucinations can take diverse forms, d…