4 citations · 7 across the 18 of their papers we have counts for
4 papers · 1 filter
Constructive Distortion: Improving MLLMs with Attention-Guided Image Warping
Dwip Dalal, Gautam Vashishtha, Utkarsh Mishra +6
Multimodal large language models (MLLMs) often miss small details and spatial relations in cluttered scenes, leading to errors in fine-grained perceptual grounding. We introduce At…
PARTONOMY: Large Multimodal Models with Part-Level Visual Understanding
Ansel Blume, Jeonghwan Kim, Hyeonjeong Ha +7
Real-world objects are composed of distinctive, object-specific parts. Identifying these parts is key to performing fine-grained, compositional reasoning-yet, large multimodal mode…
MM-PoisonRAG: Disrupting Multimodal RAG with Local and Global Poisoning Attacks
Hyeonjeong Ha, Qiusi Zhan, Jeonghwan Kim +6
Retrieval-augmented generation (RAG) has become a common practice in multimodal large language models (MLLM) to enhance factual grounding and reduce hallucination. Yet, its relianc…
SYNTHIA: Novel Concept Design with Affordance Composition
Hyeonjeong Ha, Xiaomeng Jin, Jeonghwan Kim +7
Text-to-image (T2I) models enable rapid concept design, making them widely used in AI-driven design. While recent studies focus on generating semantic and stylistic variations of g…