25 citations · 41 across the 10 of their papers we have counts for
5 papers · 1 filter
BlenderLLM: Training Large Language Models for Computer-Aided Design with Self-improvement
Yuhao Du, Shunian Chen, Wenbo Zan +6
The application of Large Language Models (LLMs) in Computer-Aided Design (CAD) remains an underexplored area, despite their remarkable advancements in other domains. In this paper,…
Exploring Compositional Generalization of Multimodal LLMs for Medical Imaging
Zhenyang Cai, Junying Chen, Rongsheng Wang +6
Medical imaging provides essential visual insights for diagnosis, and multimodal large language models (MLLMs) are increasingly utilized for its analysis due to their strong genera…
Both Text and Images Leaked! A Systematic Analysis of Data Contamination in Multimodal LLM
Dingjie Song, Sicheng Lai, Mingxuan Wang +3
The rapid advancement of multimodal large language models (MLLMs) has significantly enhanced performance across benchmarks. However, data contamination-unintentional memorization o…
LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via a Hybrid Architecture
Xidong Wang, Dingjie Song, Shunian Chen +5
Expanding the long-context capabilities of Multi-modal Large Language Models~(MLLMs) is critical for advancing video understanding and high-resolution image analysis. Achieving thi…
MileBench: Benchmarking MLLMs in Long Context
Dingjie Song, Shunian Chen, Guiming Hardy Chen +3
Despite the advancements and impressive performance of Multimodal Large Language Models (MLLMs) on benchmarks, their effectiveness in real-world, long-context, and multi-image task…