1 citations · 1 across the 8 of their papers we have counts for
8 papers
C-PTQ: Fisher-weighted Channel-wise Sensitivity for Post-training Quantization of MLLMs
Jiameng Li, Han Zhou, Matthew B. Blaschko
Multimodal large language models (MLLMs) require huge memory and computational costs, which limits their practical deployment. Post-training quantization (PTQ) techniques offer an…
EchoPrune: Interpreting Redundancy as Temporal Echoes for Efficient VideoLLMs
Jiameng Li, Minye Wu, Jiezhang Cao +2
Long-form video understanding remains challenging for Video Large Language Models (VideoLLMs), as the dense frame sampling introduces massive visual tokens while sparse sampling ri…
MI-Pruner: Crossmodal Mutual Information-guided Token Pruner for Efficient MLLMs
Jiameng Li, Aleksei Tiulpin, Matthew B. Blaschko
For multimodal large language models (MLLMs), visual information is relatively sparse compared with text. As a result, research on visual pruning emerges for efficient inference. C…
CLASH: A Benchmark for Cross-Modal Contradiction Detection
Teodora Popordanoska, Jiameng Li, Matthew B. Blaschko
Contradictory multimodal inputs are common in real-world settings, yet existing benchmarks typically assume input consistency and fail to evaluate cross-modal contradiction detecti…
YpathRAG:A Retrieval-Augmented Generation Framework and Benchmark for Pathology
Deshui Yu, Yizhi Wang, Saihui Jin +9
Large language models (LLMs) excel on general tasks yet still hallucinate in high-barrier domains such as pathology. Prior work often relies on domain fine-tuning, which neither ex…
CARE: Confidence-aware Ratio Estimation for Medical Biomarkers
Jiameng Li, Teodora Popordanoska, Aleksei Tiulpin +3
Ratio-based biomarkers (RBBs), such as the proportion of necrotic tissue within a tumor, are widely used in clinical practice to support diagnosis, prognosis, and treatment plannin…
Mipmap-GS: Let Gaussians Deform with Scale-specific Mipmap for Anti-aliasing Rendering
Jiameng Li, Yue Shi, Jiezhang Cao +4
3D Gaussian Splatting (3DGS) has attracted great attention in novel view synthesis because of its superior rendering efficiency and high fidelity. However, the trained Gaussians su…
Unveiling Incomplete Modality Brain Tumor Segmentation: Leveraging Masked Predicted Auto-Encoder and Divergence Learning
Zhongao Sun, Jiameng Li, Yuhan Wang +3
Brain tumor segmentation remains a significant challenge, particularly in the context of multi-modal magnetic resonance imaging (MRI) where missing modality images are common in cl…