8 citations · 18 across the 10 of their papers we have counts for
10 papers
LiveVLN: Breaking the Stop-and-Go Loop in Vision-Language Navigation
Xiangchen Wang, Weiye Zhu, Teng Wang +5
Recent navigation systems achieve strong benchmark results, yet real-world deployment often remains visibly stop-and-go. This bottleneck arises because the sense-inference-executio…
\textsc{NaVIDA}: Vision-Language Navigation with Inverse Dynamics Augmentation
Weiye Zhu, Zekai Zhang, Xiangchen Wang +5
Vision-and-Language Navigation (VLN) requires agents to interpret natural language instructions and act coherently in visually rich environments. However, most existing methods rel…
R-AVST: Empowering Video-LLMs with Fine-Grained Spatio-Temporal Reasoning in Complex Audio-Visual Scenarios
Lu Zhu, Tiantian Geng, Yangye Chen +3
Recently, rapid advancements have been made in multimodal large language models (MLLMs), especially in video understanding tasks. However, current research focuses on simple video…
Seeing More, Saying More: Lightweight Language Experts are Dynamic Video Token Compressors
Xiangchen Wang, Jinrui Zhang, Teng Wang +2
Recent advancements in large video-language models have revolutionized video understanding tasks. However, their efficiency is significantly constrained by processing high volumes…
LongVALE: Vision-Audio-Language-Event Benchmark Towards Time-Aware Omni-Modal Perception of Long Videos
Tiantian Geng, Jinrui Zhang, Qingni Wang +3
Despite impressive advancements in video understanding, most efforts remain limited to coarse-grained or visual-only video tasks. However, real-world videos encompass omni-modal in…
Sample then Identify: A General Framework for Risk Control and Assessment in Multimodal Large Language Models
Qingni Wang, Tiantian Geng, Zhiyuan Wang +3
Multimodal Large Language Models (MLLMs) exhibit promising advancements across various tasks, yet they still encounter significant trustworthiness issues. Prior studies apply Split…
Reflective Instruction Tuning: Mitigating Hallucinations in Large Vision-Language Models
Jinrui Zhang, Teng Wang, Haigang Zhang +2
Large vision-language models (LVLMs) have shown promising performance on a variety of vision-language tasks. However, they remain susceptible to hallucinations, generating outputs…
Two in One Go: Single-stage Emotion Recognition with Decoupled Subject-context Transformer
Xinpeng Li, Teng Wang, Jian Zhao +5
Emotion recognition aims to discern the emotional state of subjects within an image, relying on subject-centric and contextual visual cues. Current approaches typically follow a tw…
UniAV: Unified Audio-Visual Perception for Multi-Task Video Event Localization
Tiantian Geng, Teng Wang, Jinming Duan +4
Video event localization tasks include temporal action localization (TAL), sound event detection (SED) and audio-visual event localization (AVEL). Existing methods tend to over-spe…
Video Understanding with Large Language Models: A Survey
Yolo Y. Tang, Jing Bi, Siting Xu +17
With the burgeoning growth of online video platforms and the escalating volume of video content, the demand for proficient video understanding tools has intensified markedly. Given…