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Found 5 papers, 4 papers with code
An Empirical Study of Training ID-Agnostic Multi-modal Sequential Recommenders
Sequential Recommendation (SR) aims to predict future user-item interactions based on historical interactions.
Towards Robust Multi-Modal Reasoning via Model Selection
The reasoning capabilities of LLM (Large Language Model) are widely acknowledged in recent research, inspiring studies on tool learning and autonomous agents.
Towards Complex-query Referring Image Segmentation: A Novel Benchmark
Referring Image Understanding (RIS) has been extensively studied over the past decade, leading to the development of advanced algorithms.
A Content-Driven Micro-Video Recommendation Dataset at Scale
Micro-videos have recently gained immense popularity, sparking critical research in micro-video recommendation with significant implications for the entertainment, advertising, and e-commerce industries.
Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation
To be specific, we first introduce an ID-aware Multi-modal Transformer module in the item representation learning stage to facilitate information interaction among different features.
