Papers by Haneol Jang
VLR-Bench: Multilingual Benchmark Dataset for Vision-Language Retrieval Augmented Generation (2025.coling-main)
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Hyeonseok Lim, Dongjae Shin, Seohyun Song, Inho Won, Minjun Kim, Junghun Yuk, Haneol Jang, KyungTae Lim
| Challenge: | Existing evaluation datasets for external knowledge-based VQA lack a capability to determine which passage is useful for answering queries. |
| Approach: | They propose a visual question answering benchmark for vision language models based on retrieval augmented generation (RAG) the proposed benchmark includes five input passages, a capability lacking in previous research. |
| Outcome: | The proposed benchmark includes five input passages and is validated using the state-of-the-art Llama3-based VLM, the Llava-Llamama-3 model. |