2026
URaG: Unified Retrieval and Generation in Multimodal LLMs for Efficient Long Document Understanding
AAAI 2026technical
Recent multimodal large language models (MLLMs) still struggle with long document understanding due to two fundamental challenges: information interference from abundant irrelevant content, and the quadratic computational cost of Transformer-based architectures. Existing approaches primarily fall in