1 citations · 1 across the 13 of their papers we have counts for
15 papers
AirGroundVLN: A Large-Scale Benchmark for Goal-Oriented Air-Ground Collaborative Vision-and-Language Navigation
Zhenxuan Zeng, Qingle Wu, Wei Suo +4
Goal-oriented Vision-and-Language Navigation (VLN) requires agents to locate and reach targets described in natural language without prescribed routes. Air--ground collaboration is…
GSMap: 2D Gaussians for Online HD Mapping
Zhenxuan Zeng, Lingxuan Wang, Sheng Yang +4
Accurate High-Definition (HD) map construction is critical for autonomous driving, yet existing methods face a fundamental trade-off: vectorization-based approaches preserve topolo…
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…
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…
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…
CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning
Yukun Li, Guansong Pang, Wei Suo +6
This paper explores the problem of continual learning (CL) of vision-language models (VLMs) in open domains, where the models need to perform continual updating and inference on a…
S3C: Semi-Supervised VQA Natural Language Explanation via Self-Critical Learning
Wei Suo, Mengyang Sun, Weisong Liu +4
VQA Natural Language Explanation (VQA-NLE) task aims to explain the decision-making process of VQA models in natural language. Unlike traditional attention or gradient analysis, fr…
Dual-Level Decoupled Transformer for Video Captioning
Yiqi Gao, Xinglin Hou, Wei Suo +4
Video captioning aims to understand the spatio-temporal semantic concept of the video and generate descriptive sentences. The de-facto approach to this task dictates a text generat…
Proposal-free One-stage Referring Expression via Grid-Word Cross-Attention
Wei Suo, Mengyang Sun, Peng Wang +1
Referring Expression Comprehension (REC) has become one of the most important tasks in visual reasoning, since it is an essential step for many vision-and-language tasks such as vi…