2 citations · 2 across the 10 of their papers we have counts for
9 papers · 1 filter
MM-OPD: Towards One More Bottleneck Between Perception and Reasoning
Jintao Tong, Yujing Lou, Zhanming Shen +6
Recent multimodal large language models (MLLMs) advance visual reasoning by strengthening both perception and reasoning, implicitly assuming a process that transitions seamlessly f…
Shallow to Deep: Aligning Token Pruning with Stage-wise Roles in LVLMs
Shuo Zhang, Jintao Tong, Yixiong Zou +2
Large Vision-Language Models (LVLMs) incur high computational costs from redundant visual tokens. Although training-free attention-based multi-layer pruning in the vision encoder s…
Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models
Shilin Yan, Jintao Tong, Hongwei Xue +6
The advent of agentic multimodal models has empowered systems to actively interact with external environments. However, current agents suffer from a profound meta-cognitive deficit…
SwimBird: Eliciting Switchable Reasoning Mode in Hybrid Autoregressive MLLMs
Jintao Tong, Shilin Yan, Hongwei Xue +5
Multimodal Large Language Models (MLLMs) have made remarkable progress in multimodal perception and reasoning by bridging vision and language. However, most existing MLLMs perform…
Sketch-in-Latents: Eliciting Unified Reasoning in MLLMs
Jintao Tong, Jiaqi Gu, Yujing Lou +5
While Multimodal Large Language Models (MLLMs) excel at visual understanding tasks through text reasoning, they often fall short in scenarios requiring visual imagination. Unlike c…
Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
Jintao Tong, Ran Ma, Yixiong Zou +3
Cross-domain few-shot segmentation (CD-FSS) is proposed to pre-train the model on a source-domain dataset with sufficient samples, and then transfer the model to target-domain data…
Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
Jintao Tong, Yixiong Zou, Guangyao Chen +2
Cross-Domain Few-Shot Segmentation (CD-FSS) aims to transfer knowledge from a source-domain dataset to unseen target-domain datasets with limited annotations. Current methods typic…
FlowCut: Rethinking Redundancy via Information Flow for Efficient Vision-Language Models
Jintao Tong, Wenwei Jin, Pengda Qin +5
Large vision-language models (LVLMs) excel at multimodal understanding but suffer from high computational costs due to redundant vision tokens. Existing pruning methods typically r…
Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation
Jintao Tong, Yixiong Zou, Yuhua Li +1
Cross-domain few-shot segmentation (CD-FSS) is proposed to first pre-train the model on a large-scale source-domain dataset, and then transfer the model to data-scarce target-domai…