1 citations · 2 across the 11 of their papers we have counts for
12 papers
Hallucination-aware intermediate representation edit in large vision-language models
Wei Suo, Hanzu Zhang, Lijun Zhang +3
Large Vision-Language Models have demonstrated exceptional performance in multimodal reasoning and complex scene understanding. However, these models still face significant halluci…
Understanding and Mitigating Hallucinations in Multimodal Chain-of-Thought Models
Ji Ma, Wei Suo, Peng Wang +1
Multimodal Chain-of-Thought (MCoT) models have demonstrated impressive capability in complex visual reasoning tasks. Unfortunately, recent studies reveal that they suffer from seve…
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models
Mingyu Fu, Wei Suo, Ji Ma +3
Despite the great success of Large Vision Language Models (LVLMs), their high computational cost severely limits their broad applications. The computational cost of LVLMs mainly st…
Short-LVLM: Compressing and Accelerating Large Vision-Language Models by Pruning Redundant Layers
Ji Ma, Wei Suo, Peng Wang +1
Although large vision-language models (LVLMs) have demonstrated impressive capabilities in multi-modal understanding and reasoning, their practical applications are still limited b…
Language Embedding Meets Dynamic Graph: A New Exploration for Neural Architecture Representation Learning
Haizhao Jing, Haokui Zhang, Zhenhao Shang +3
Neural Architecture Representation Learning aims to transform network models into feature representations for predicting network attributes, playing a crucial role in deploying and…
DiffV2IR: Visible-to-Infrared Diffusion Model via Vision-Language Understanding
Lingyan Ran, Lidong Wang, Guangcong Wang +2
The task of translating visible-to-infrared images (V2IR) is inherently challenging due to three main obstacles: 1) achieving semantic-aware translation, 2) managing the diverse wa…
Octopus: Alleviating Hallucination via Dynamic Contrastive Decoding
Wei Suo, Lijun Zhang, Mengyang Sun +3
Large Vision-Language Models (LVLMs) have obtained impressive performance in visual content understanding and multi-modal reasoning. Unfortunately, these large models suffer from s…
Pruning All-Rounder: Rethinking and Improving Inference Efficiency for Large Vision Language Models
Wei Suo, Ji Ma, Mengyang Sun +3
Although Large Vision-Language Models (LVLMs) have achieved impressive results, their high computational costs pose a significant barrier to wide application. To enhance inference…
Contourlet Refinement Gate Framework for Thermal Spectrum Distribution Regularized Infrared Image Super-Resolution
Yang Zou, Zhixin Chen, Zhipeng Zhang +5
Image super-resolution (SR) is a classical yet still active low-level vision problem that aims to reconstruct high-resolution (HR) images from their low-resolution (LR) counterpart…
A Plug-and-Play Method for Rare Human-Object Interactions Detection by Bridging Domain Gap
Lijun Zhang, Wei Suo, Peng Wang +1
Human-object interactions (HOI) detection aims at capturing human-object pairs in images and corresponding actions. It is an important step toward high-level visual reasoning and s…
Visual Prompt Selection for In-Context Learning Segmentation
Wei Suo, Lanqing Lai, Mengyang Sun +3
As a fundamental and extensively studied task in computer vision, image segmentation aims to locate and identify different semantic concepts at the pixel level. Recently, inspired…
C3L: Content Correlated Vision-Language Instruction Tuning Data Generation via Contrastive Learning
Ji Ma, Wei Suo, Peng Wang +1
Vision-Language Instruction Tuning (VLIT) is a critical training phase for Large Vision-Language Models (LVLMs). With the improving capabilities of open-source LVLMs, researchers h…