arXiv:2501.02235
Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends
원문 초록
Using Large Language Models (LLMs) for Visually-rich Document Understanding (VrDU) has significantly improved performance on tasks requiring both comprehension and generation, such as question answering, albeit introducing new challenges. This survey explains how VrDU models enhanced by LLMs function, covering methods for integrating VrD features into LLMs and highlighting key challenges.
함께 살펴볼 논문
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DrishtiKon: Multi-Granular Visual Grounding for Text-Rich Document Images
SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement
WikiMixQA: A Multimodal Benchmark for Question Answering over Tables and Charts
From Roots to Rewards: Dynamic Tree Reasoning with RL
Describe Anything Model for Visual Question Answering on Text-rich Images
Warehouse Spatial Question Answering with LLM Agent
토론
이 논문과 연결된 포럼 글이 아직 없습니다.