## WINGS: A New Approach to Prevent Text-Only Forgetting in Multimodal LLMs This article introduces WINGS, a novel architecture designed to address a key challenge in multimodal large langu…
## WINGS: A New Approach to Prevent Text-Only Forgetting in Multimodal LLMs This article introduces WINGS, a novel architecture designed to address a key challenge in multimodal large language models (MLLMs). The research highlights the problem of "text-only forgetting" that arises when incorporating visual information into these advanced AI systems.
### The Rise of Multimodal LLMs MLLMs are transforming AI by enabling systems to process and understand both text and images. This allows for more engaging and versatile AI applications, including: * Answering questions about images * Generating content that combines text and visuals * Creating more intuitive and interactive AI assistants Their ability to connect visual and linguistic information makes them increasingly important in fields like education and content creation.
### Addressing Text-Only Forgetting The core issue tackled by WINGS is **text-only forgetting**. This refers to the tendency of MLLMs to lose their proficiency in processing text as they are trained to also handle visual data. WINGS solves this problem by implementing a **dual-learner architecture**.
This architecture integrates visual and textual learners using **low-rank residual attention**. This design helps maintain the LLM's ability to process text while also incorporating visual information.