2 citations · 5 across the 12 of their papers we have counts for
12 papers
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…
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…
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…
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…
FlowSteer: Conditioning Flow Field for Consistent Image Restoration
Tharindu Wickremasinghe, Chenyang Qi, Harshana Weligampola +2
Flow-based text-to-image (T2I) models excel at prompt-driven image generation, but falter on Image Restoration (IR), often "drifting away" from being faithful to the measurement. P…
Noisy-Pair Robust Representation Alignment for Positive-Unlabeled Learning
Hengwei Zhao, Zhengzhong Tu, Zhuo Zheng +4
Positive-Unlabeled (PU) learning aims to train a binary classifier (positive vs. negative) where only limited positive data and abundant unlabeled data are available. While widely…