7 papers
ActiveScope: Actively Seeking and Correcting Perception for MLLMs
Yajing Wang, Chao Bi, Junshu Sun +4
Multimodal Large Language Models (MLLMs) have demonstrated impressive vision-language understanding, yet still struggle with fine-grained perception in high-resolution images. Whil…
STAND: Semantic Anchoring Constraint with Dual-Granularity Disambiguation for Remote Sensing Image Change Captioning
Yanpei Gong, Beichen Zhang, Hao Wang +6
Remote sensing image change captioning (RSICC) aims to describe the difference between two remote sensing images. While recent methods have explored video modeling, they largely ov…
AIFIND: Artifact-Aware Interpreting Fine-Grained Alignment for Incremental Face Forgery Detection
Hao Wang, Beichen Zhang, Yanpei Gong +5
As forgery types continue to emerge consistently, Incremental Face Forgery Detection (IFFD) has become a crucial paradigm. However, existing methods typically rely on data replay o…
SinkRouter: Sink-Aware Routing for Efficient Long-Context Decoding in Large Language and Multimodal Models
Junnan Liu, Xinyan Liu, Peifeng Gao +4
In long-context decoding for LLMs and LMMs, attention becomes increasingly memory-bound because each decoding step must load a large amount of KV-cache data from GPU memory. Existi…
TowerDataset: A Heterogeneous Benchmark for Transmission Corridor Segmentation with a Global-Local Fusion Framework
Xu Cui, Xinyan Liu, Chen Yang +4
Fine-grained semantic segmentation of transmission-corridor point clouds is fundamental for intelligent power-line inspection. However, current progress is limited by realistic dat…
Enhancing Pre-trained Representation Classifiability can Boost its Interpretability
Shufan Shen, Zhaobo Qi, Junshu Sun +3
The visual representation of a pre-trained model prioritizes the classifiability on downstream tasks, while the widespread applications for pre-trained visual models have posed new…