Evolution of Multimodal Question Answering: From Modality-Adaptive Extraction to Unified Language Representation
The rapid growth of multimodal data has intensified the need for question answering (QA) systems capable of reasoning across heterogeneous sources such as text, tables, and images. In this paper, we present a comprehensive methodological comparison of three influential frameworks, namely Multimodal Adaptive Extraction (MAE), Solar, and UniMMQA, tracing the evolution of multimodal question answering from modality-adaptive pipelines to fully unified architectures. We examine how each approach models cross-modal interactions, transforms heterogeneous inputs, and performs reasoning, highlighting key design differences in modality representation, reasoning, and answer generation. Our analysis ...
| Authors | Abdullah Al Shafi |
|---|---|
| Primary category | cs.CL |
| Published | 8 September 2026 |
| Last updated at source | 8 September 2026 |
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