2 citations · 2 across the 8 of their papers we have counts for
9 papers
Training Agents to Evolve with Their Harness: TaoLive Digital Avatar Agent Technical Report
TaoLive AIGC LLM Team, Yuhan Sun, Wenhao Lin +7
AI-powered digital avatar streamers must answer product questions, engage viewers, and execute marketing strategies in real time, demanding low latency, frequent strategy updates,…
TLive-Omni: An Omni-Modal Understanding Model for E-Commerce Live Streaming
Yibo Hu, Yu Qian, Mao Gu +6
E-commerce live streaming requires omni-modal understanding of noisy, temporally extended streams, where product facts are distributed across speech, video frames, product images,…
WaveZip: Wavelet-Driven Space-Time Decoupling for Video Token Condensation
Yuhui Zeng, Wang Chen, Jinfa Huang +5
Existing Large Vision-Language Models (LVLMs) struggle with long-form video understanding due to the quadratic computational cost of visual tokens. While recent efficient methods a…
OmniScope: Modality-Decoupled Token Compression for Omnimodal Large Language Models
Jinsen Su, Yongdong Luo, Yuexiao Ma +3
Existing token compression methods for omnimodal large language models typically rely on one modality to determine what to retain in the other. We show that this assumption often b…
Watch Where You Move: Region-aware Dynamic Aggregation and Excitation for Gait Recognition
Binyuan Huang, Yongdong Luo, Xianda Guo +4
Deep learning-based gait recognition has achieved great success in various applications. The key to accurate gait recognition lies in considering the unique and diverse behavior pa…
QuoTA: Query-oriented Token Assignment via CoT Query Decouple for Long Video Comprehension
Yongdong Luo, Wang Chen, Xiawu Zheng +8
Recent advances in long video understanding typically mitigate visual redundancy through visual token pruning based on attention distribution. However, while existing methods emplo…
Video-RAG: Visually-aligned Retrieval-Augmented Long Video Comprehension
Yongdong Luo, Xiawu Zheng, Guilin Li +8
Existing large video-language models (LVLMs) struggle to comprehend long videos correctly due to limited context. To address this problem, fine-tuning long-context LVLMs and employ…
Rethinking 3D Dense Caption and Visual Grounding in A Unified Framework through Prompt-based Localization
Yongdong Luo, Haojia Lin, Xiawu Zheng +6
3D Visual Grounding (3DVG) and 3D Dense Captioning (3DDC) are two crucial tasks in various 3D applications, which require both shared and complementary information in localization…
A Unified Framework for 3D Point Cloud Visual Grounding
Haojia Lin, Yongdong Luo, Xiawu Zheng +7
Thanks to its precise spatial referencing, 3D point cloud visual grounding is essential for deep understanding and dynamic interaction in 3D environments, encompassing 3D Referring…