4 citations · 4 across the 12 of their papers we have counts for
6 papers · 1 filter
Beyond Chain-of-Thought: Rewrite as a Universal Interface for Generative Multimodal Embeddings
Peixi Wu, Ke Mei, Feipeng Ma +15
Multimodal Large Language Models (MLLMs) have emerged as a promising foundation for universal multimodal embeddings. Recent studies have shown that reasoning-driven generative mult…
Countering the Over-Reliance Trap: Mitigating Object Hallucination for LVLMs via a Self-Validation Framework
Shiyu Liu, Xinyi Wen, Zhibin Lan +2
Despite progress in Large Vision Language Models (LVLMs), object hallucination remains a critical issue in image captioning task, where models generate descriptions of non-existent…
PATIMT-Bench: A Multi-Scenario Benchmark for Position-Aware Text Image Machine Translation in Large Vision-Language Models
Wanru Zhuang, Wenbo Li, Zhibin Lan +3
Text Image Machine Translation (TIMT) aims to translate texts embedded within an image into another language. Current TIMT studies primarily focus on providing translations for all…
LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning
Zhibin Lan, Liqiang Niu, Fandong Meng +2
Universal multimodal embedding models play a critical role in tasks such as interleaved image-text retrieval, multimodal RAG, and multimodal clustering. However, our empirical resu…
Empowering Backbone Models for Visual Text Generation with Input Granularity Control and Glyph-Aware Training
Wenbo Li, Guohao Li, Zhibin Lan +5
Diffusion-based text-to-image models have demonstrated impressive achievements in diversity and aesthetics but struggle to generate images with legible visual texts. Existing backb…
AVG-LLaVA: An Efficient Large Multimodal Model with Adaptive Visual Granularity
Zhibin Lan, Liqiang Niu, Fandong Meng +3
Recently, large multimodal models (LMMs) have achieved significant advancements. When dealing with high-resolution images, dominant LMMs typically divide them into multiple local i…