2 citations · 2 across the 8 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.LG2026
MoEMB: Scaling Universal Multimodal Embeddings with Efficient Mixture-of-Experts Models
Xuanming Cui, Shlok Kumar Mishra, Wentao Bao +6
Universal multimodal embedding (UME) increasingly demands encoder's capacity for handling a broad range of tasks and modalities with increased complexity. Prior scaling methods eit…
cs.CV2026
BOOKAGENT: Orchestrating Safety-Aware Visual Narratives via Multi-Agent Cognitive Calibration
Bo Gao, Chang Liu, Yuyang Miao +2
Recent advancements in Large Generative Models (LGMs) have revolutionized multi-modal generation. However, generating illustrated storybooks remains an open challenge, where prior…
cs.IR2026
Reason to Contrast: A Cascaded Multimodal Retrieval Framework
Xuanming Cui, Hong-You Chen, Hao Yu +10
Traditional multimodal retrieval systems rely primarily on bi-encoder architectures, where performance is closely tied to embedding dimensionality. Recent work, Think-Then-Embed (T…