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20232026
most citedBigger is not Always Better: Scaling Properties of Latent Diffusion Models

2 citations · 5 across the 12 of their papers we have counts for

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cs.IR2026

OpticalRec: Unified Optical Vision-Language Representation for Multimodal Recommendation

Yueqi Wang, Zitian Guo, Yupeng Hou +9

Recent advances in vision-language modeling have substantially improved multimodal encoding, retrieval and reasoning. Yet for multimodal recommendation, encoding rich item vision-l…

cs.DC2026

FlashDiff: Efficient Regional Execution and Scheduling for Diffusion Model Serving

Yaqi Qiao, Ping He, Songrun Xie +4

Diffusion models have become the central backbone for modern image, video, and audio generation, but their efficient service remains a challenge. Unlike autoregressive decoding, di…

cs.CR2026

Cert-LAS: Toward Certified Model Ownership Verification for Text-to-Image Diffusion Models via Layer-Adaptive Smoothing

Leyi Qi, Yiming Li, Siyuan Liang +2

Large-scale text-to-image (T2I) diffusion models have enabled unprecedented creative applications, but their unauthorized use has raised serious intellectual property concerns, mak…

cs.CV2026

Region-R1: Reinforcing Query-Side Region Cropping for Multi-Modal Re-Ranking

Chan-Wei Hu, Zhengzhong Tu

Multi-modal retrieval-augmented generation (MM-RAG) relies heavily on re-rankers to surface the most relevant evidence for image-question queries. However, standard re-rankers typi…

cs.CL2026

FASA: Frequency-aware Sparse Attention

Yifei Wang, Yueqi Wang, Zhenrui Yue +6

The deployment of Large Language Models (LLMs) faces a critical bottleneck when handling lengthy inputs: the prohibitive memory footprint of the Key Value (KV) cache. To address th…