activity
20232026
most citedExpanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

16 citations · 17 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning

Xuehui Wang, Xuankun Yang, Wei Shen

Visual token pruning is a crucial strategy for accelerating VLMs by compressing redundant image patches, yet existing methods often fail to preserve critical cues under dense instr…

cs.LG2025

Generalized Tensor-based Parameter-Efficient Fine-Tuning via Lie Group Transformations

Chongjie Si, Zhiyi Shi, Xuehui Wang +3

Adapting pre-trained foundation models for diverse downstream tasks is a core practice in artificial intelligence. However, the wide range of tasks and high computational costs mak…

cs.CV2024★ 16 cited

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Zhe Chen, Weiyun Wang, Yue Cao +39

We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing signif…

cs.CV2024★ 1 cited

Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning

Chongjie Si, Xuehui Wang, Xue Yang +6

Adapting pre-trained foundation models for various downstream tasks has been prevalent in artificial intelligence. Due to the vast number of tasks and high costs, adjusting all par…

cs.CV2024

Tendency-driven Mutual Exclusivity for Weakly Supervised Incremental Semantic Segmentation

Chongjie Si, Xuehui Wang, Xiaokang Yang +1

Weakly Incremental Learning for Semantic Segmentation (WILSS) leverages a pre-trained segmentation model to segment new classes using cost-effective and readily available image-lev…

cs.LG2023

Appeal: Allow Mislabeled Samples the Chance to be Rectified in Partial Label Learning

Chongjie Si, Xuehui Wang, Yan Wang +2

In partial label learning (PLL), each instance is associated with a set of candidate labels among which only one is ground-truth. The majority of the existing works focuses on cons…

cs.CV2023

Bridging Synthetic and Real Worlds for Pre-training Scene Text Detectors

Tongkun Guan, Wei Shen, Xue Yang +2

Existing scene text detection methods typically rely on extensive real data for training. Due to the lack of annotated real images, recent works have attempted to exploit large-sca…