![[阅读笔记21][RA-CM3]Retrieval-Augmented Multimodal Language Modeling ...](https://img-blog.csdnimg.cn/direct/b0b9560fcbca4bce9684b9b006faeb89.png)
![[阅读笔记21][RA-CM3]Retrieval-Augmented Multimodal Language Modeling-CSDN博客](https://i-blog.csdnimg.cn/blog_migrate/10e7524c338bedf7adc43dfeb0daf6c1.png)
![[论文阅读笔记]Feature fusion and latent feature learning guided brain tumor ...](https://img-blog.csdnimg.cn/img_convert/8819c16c790027580f137472882e997f.png)
![[Information Fusion] Rethinking multi-exposure image fusion with ...](https://miccai.fudan.edu.cn/_upload/article/images/ee/2f/6dfcddea4277b0d57b9b13bca02e/aaebdc06-a474-4fac-8506-d80df08ab34e.png)
%20excel%20in%20generating%20responses%20based%20on%20visual%20inputs.%20However%2C%20they%20often%20suffer%20from%20a%20bias%20towards%20generating%20responses%20similar%20to%20their%20pretraining%20corpus%2C%20overshadowing%20the%20importance%20of%20visual%20information.%20We%20treat%20this%20bias%20as%20a%20preference%20for%20pretraining%20statistics%2C%20which%20hinders%20the%20model's%20grounding%20in%20visual%20input.%20To%20mitigate%20this%20issue%2C%20we%20propose%20Bootstrapped%20Preference%20Optimization%20(BPO)%2C%20which%20conducts%20preference%20learning%20with%20datasets%20containing%20negative%20responses%20bootstrapped%20from%20the%20model%20itself.%20Specifically%2C%20we%20propose%20the%20following%20two%20strategies:%201)%20using%20distorted%20image%20inputs%20to%20the%20MLLM%20for%20eliciting%20responses%20that%20contain%20signified%20pretraining%20bias%3B%202)%20leveraging%20text-based%20LLM%20to%20explicitly%20inject%20erroneous%20but%20common%20elements%20into%20the%20original%20response.%20Those%20undesirable%20responses%20are%20paired%20with%20original%20annotated%20responses%20from%20the%20datasets%20to%20construct%20the%20preference%20dataset%2C%20which%20is%20subsequently%20utilized%20to%20perform%20preference%20learning.%20Our%20approach%20effectively%20suppresses%20pretrained%20LLM%20bias%2C%20enabling%20enhanced%20grounding%20in%20visual%20inputs.%20Extensive%20experimentation%20demonstrates%20significant%20performance%20improvements%20across%20multiple%20benchmarks%2C%20advancing%20the%20state-of-the-art%20in%20multimodal%20conversational%20systems.)
Experience the timeless beauty of furu wei on linkedin: multimodal latent language modeling with next with our curated gallery of numerous images. highlighting the retro appeal of photography, images, and pictures. designed to evoke timeless elegance. Each furu wei on linkedin: multimodal latent language modeling with next image is carefully selected for superior visual impact and professional quality. Suitable for various applications including web design, social media, personal projects, and digital content creation All furu wei on linkedin: multimodal latent language modeling with next images are available in high resolution with professional-grade quality, optimized for both digital and print applications, and include comprehensive metadata for easy organization and usage. Our furu wei on linkedin: multimodal latent language modeling with next gallery offers diverse visual resources to bring your ideas to life. Reliable customer support ensures smooth experience throughout the furu wei on linkedin: multimodal latent language modeling with next selection process. Instant download capabilities enable immediate access to chosen furu wei on linkedin: multimodal latent language modeling with next images. Regular updates keep the furu wei on linkedin: multimodal latent language modeling with next collection current with contemporary trends and styles. Professional licensing options accommodate both commercial and educational usage requirements.