Large Language Model
Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality
Despite these strides, evaluating these models poses substantial challenges.
Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal Models Y ang Jiao
The current methods follow the paradigm of adapting the visual task outputs to language-oriented formats.
Mesa-Extrapolation: A Weave Position Encoding Method for Enhanced Extrapolation in LLMs
LLMs sharply declines beyond their max training lengths.
Multimodal Large Language Models Make Text-to-Image Generative Models Align Better Xun Wu
Preference data is crucial for aligning generative models with text prompts.
Segment Any Change
We perform extensive experiments to confirm the effectiveness of AnyChange for zero-shot change detection.
Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP
Large pretrained vision-language models like CLIP have shown promising generalization capability, but may struggle in specialized domains ( e.g., satellite imagery)
