4 citations · 6 across the 7 of their papers we have counts for
7 papers
Suppressing Prior-Comparison Hallucinations in Radiology Report Generation via Semantically Decoupled Latent Steering
Ao Li, Rui Liu, Mingjie Li +6
Automated radiology report generation using vision-language models (VLMs) is limited by the risk of prior-comparison hallucination, where the model generates historical findings un…
Flexiffusion: Training-Free Segment-Wise Neural Architecture Search for Efficient Diffusion Models
Hongtao Huang, Xiaojun Chang, Lina Yao
Diffusion models (DMs) are powerful generative models capable of producing high-fidelity images but are constrained by high computational costs due to iterative multi-step inferenc…
Dual Conditional Diffusion Models for Sequential Recommendation
Hongtao Huang, Chengkai Huang, Tong Yu +4
Recent advancements in diffusion models have shown promising results in sequential recommendation (SR). Existing approaches predominantly rely on implicit conditional diffusion mod…
Flexiffusion: Segment-wise Neural Architecture Search for Flexible Denoising Schedule
Hongtao Huang, Xiaojun Chang, Lina Yao
Diffusion models are cutting-edge generative models adept at producing diverse, high-quality images. Despite their effectiveness, these models often require significant computation…
MatchNAS: Optimizing Edge AI in Sparse-Label Data Contexts via Automating Deep Neural Network Porting for Mobile Deployment
Hongtao Huang, Xiaojun Chang, Wen Hu +1
Recent years have seen the explosion of edge intelligence with powerful Deep Neural Networks (DNNs). One popular scheme is training DNNs on powerful cloud servers and subsequently…
Mask Propagation for Efficient Video Semantic Segmentation
Yuetian Weng, Mingfei Han, Haoyu He +4
Video Semantic Segmentation (VSS) involves assigning a semantic label to each pixel in a video sequence. Prior work in this field has demonstrated promising results by extending im…
Simple Primitives with Feasibility- and Contextuality-Dependence for Open-World Compositional Zero-shot Learning
Zhe Liu, Yun Li, Lina Yao +4
The task of Compositional Zero-Shot Learning (CZSL) is to recognize images of novel state-object compositions that are absent during the training stage. Previous methods of learnin…