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Found 5 papers, 3 papers with code
MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
To this end, we introduce MathVerse, an all-around visual math benchmark designed for an equitable and in-depth evaluation of MLLMs.
MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-wise Pruning Error Metric
We find that directly using smaller pre-trained models and applying magnitude-based pruning on CLIP models leads to inflexibility and inferior performance.
IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact
Large language models (LLMs) excel in natural language processing but demand intensive computation.
Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining
In MOTOR, we combine two kinds of basic medical knowledge, i. e., general and specific knowledge, in a complementary manner to boost the general pretraining process.
Dynamic Graph Enhanced Contrastive Learning for Chest X-ray Report Generation
To address the limitation, we propose a knowledge graph with Dynamic structure and nodes to facilitate medical report generation with Contrastive Learning, named DCL.
