12 citations · 78 across the 49 of their papers we have counts for
23 papers · 1 filter
LTM: Large-scale Terrain Model for Wildfire-prone Landscapes
Xiao Fu, Yue Hu, Meida Chen +2
Accurate 3D terrain maps are essential for emergency response when assessing wildfire hazards. However, wildfire-prone regions often span vast areas where conventional reconstructi…
MemRoPE: Training-Free Infinite Video Generation via Evolving Memory Tokens
Youngrae Kim, Qixin Hu, C. -C. Jay Kuo +1
Autoregressive diffusion enables real-time frame streaming, yet existing sliding-window caches discard past context, causing fidelity degradation, identity drift, and motion stagna…
RedVTP: Training-Free Acceleration of Diffusion Vision-Language Models Inference via Masked Token-Guided Visual Token Pruning
Jingqi Xu, Jingxi Lu, Chenghao Li +3
Vision-Language Models (VLMs) have achieved remarkable progress in multimodal reasoning and generation, yet their high computational demands remain a major challenge. Diffusion Vis…
HIVTP: A Training-Free Method to Improve VLMs Efficiency via Hierarchical Visual Token Pruning Using Middle-Layer-Based Importance Score
Jingqi Xu, Jingxi Lu, Chenghao Li +2
Vision-Language Models (VLMs) have shown strong capabilities on diverse multimodal tasks. However, the large number of visual tokens output by the vision encoder severely hinders i…
FPAN: Mitigating Replication in Diffusion Models through the Fine-Grained Probabilistic Addition of Noise to Token Embeddings
Jingqi Xu, Chenghao Li, Yuke Zhang +1
Diffusion models have demonstrated remarkable potential in generating high-quality images. However, their tendency to replicate training data raises serious privacy concerns, parti…
Mitigating Hallucinations in Vision-Language Models through Image-Guided Head Suppression
Sreetama Sarkar, Yue Che, Alex Gavin +2
Despite their remarkable progress in multimodal understanding tasks, large vision language models (LVLMs) often suffer from "hallucinations", generating texts misaligned with the v…