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Si Shi

3 accepted papers

2026

SCENERAG: SCENE-LEVEL RETRIEVAL-AUGMENTED GENERATION FOR VIDEO UNDERSTANDING

ICASSP 2026poster

Despite recent advances in retrieval-augmented generation (RAG) for video understanding, effectively understanding long-form video content remains underexplored due to the vast scale and high complexity of video data. Current RAG approaches typically segment videos into fixed-length chunks, which of…

Cited by 0SourcePDFScholar
2025

Subgraph Invariant Learning Towards Large-Scale Graph Node Classification

AAAI 2025technical

Graph Neural Networks (GNNs) have shown efficacy in graph node classification, but face computational challenges on large-scale graphs. Although existing graph reduction methods address these issues, they still require high computational resources and fail to prioritize robust performance on out-of-…

2024

LGMRec: Local and Global Graph Learning for Multimodal Recommendation

AAAI 2024technical

The multimodal recommendation has gradually become the infrastructure of online media platforms, enabling them to provide personalized service to users through a joint modeling of user historical behaviors (e.g., purchases, clicks) and item various modalities (e.g., visual and textual). The majority…