Search Results for author:
Found 10 papers, 6 papers with code
TokenCarve: Information-Preserving Visual Token Compression in Multimodal Large Language Models
This insight introduces a novel information-preserving perspective, making it possible to maintain performance even under extreme token compression.
DeRS: Towards Extremely Efficient Upcycled Mixture-of-Experts Models
Upcycled Mixture-of-Experts (MoE) models have shown great potential in various tasks by converting the original Feed-Forward Network (FFN) layers in pre-trained dense models into MoE layers.
$Δ$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers
Based on this insight, we propose an overall training-free inference acceleration framework $\Delta$-DiT: using a designed cache mechanism to accelerate the rear DiT blocks in the early sampling stages and the front DiT blocks in the later stages.
MADTP: Multimodal Alignment-Guided Dynamic Token Pruning for Accelerating Vision-Language Transformer
To this end, we propose a novel framework named Multimodal Alignment-Guided Dynamic Token Pruning (MADTP) for accelerating various VLTs.
ClipSAM: CLIP and SAM Collaboration for Zero-Shot Anomaly Segmentation
Recently, foundational models such as CLIP and SAM have shown promising performance for the task of Zero-Shot Anomaly Segmentation (ZSAS).
Collaborative Position Reasoning Network for Referring Image Segmentation
Holi integrates features of the two modalities by a cross-modal attention mechanism, which suppresses the irrelevant redundancy under the guide of positioning information from RoCo.
LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark
To the best of our knowledge, we present one of the very first open-source endeavors in the field, LAMM, encompassing a Language-Assisted Multi-Modal instruction tuning dataset, framework, and benchmark.
A2S-NAS: Asymmetric Spectral-Spatial Neural Architecture Search For Hyperspectral Image Classification
To address the above issues, we propose a multi-stage search architecture in order to overcome asymmetric spectral-spatial dimensions and capture significant features.
Hyperspectral Image Classification
Neural Architecture Search
JNDMix: JND-Based Data Augmentation for No-reference Image Quality Assessment
Despite substantial progress in no-reference image quality assessment (NR-IQA), previous training models often suffer from over-fitting due to the limited scale of used datasets, resulting in model performance bottlenecks.
Bilateral Cross-Modality Graph Matching Attention for Feature Fusion in Visual Question Answering
In this paper, we focus on these two problems and propose a Graph Matching Attention (GMA) network.
