Yeji Park — accepted AI-conference papers

2026

Enhancing Multi-Image Understanding through Delimiter Token Scaling

Minyoung Lee, Yeji Park, Dongjun Hwang, Yejin Kim, Seong Joon Oh, Junsuk Choe

ICLR 2026poster

Large Vision-Language Models (LVLMs) achieve strong performance on single-image tasks, but their performance declines when multiple images are provided as input. One major reason is the cross-image information leakage, where the model struggles to distinguish information across different images. Exi…

Cited by 0 Source ↗code ↗Scholar ↗

2025

ConVis: Contrastive Decoding with Hallucination Visualization for Mitigating Hallucinations in Multimodal Large Language Models

Yeji Park, Deokyeong Lee, Junsuk Choe, Buru Chang

AAAI 2025technical

Hallucinations in Multimodal Large Language Models (MLLMs) where generated responses fail to accurately reflect the given image pose a significant challenge to their reliability. To address this, we introduce ConVis, a novel training-free contrastive decoding method. ConVis leverages a text-to-image…

Cited by 5 Source ↗PDF ↗code ↗Scholar ↗