Bayesian Natural Gradient Fine-Tuning of CLIP Models via Kalman Filtering
"视觉语言任务" 相关文章
Adapting Interleaved Encoders with PPO for Language-Guided Reinforcement Learning in BabyAI
Mitigating Coordinate Prediction Bias from Positional Encoding Failures
Rethinking the Text-Vision Reasoning Imbalance in MLLMs through the Lens of Training Recipes
GranViT: A Fine-Grained Vision Model With Autoregressive Perception For MLLMs
EMRRG: Efficient Fine-Tuning Pre-trained X-ray Mamba Networks for Radiology Report Generation
FOSSIL: Harnessing Feedback on Suboptimal Samples for Data-Efficient Generalisation with Imitation Learning for Embodied Vision-and-Language Tasks
LUQ: Layerwise Ultra-Low Bit Quantization for Multimodal Large Language Models
Revolutionizing Vision-Language Tasks with Sparse Attention Vectors: A Lightweight Approach to Discriminative Classification
Google AI Introduces LAuReL (Learned Augmented Residual Layer): Revolutionizing Neural Networks with Enhanced Residual Connections for Efficient Model Performance
Leopard: A Multimodal Large Language Model (MLLM) Designed Specifically for Handling Vision-Language Tasks Involving Multiple Text-Rich Images
