1 citations · 2 across the 14 of their papers we have counts for
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Activating Distributed Visual Region within LLMs for Efficient and Effective Vision-Language Training and Inference
Siyuan Wang, Dianyi Wang, Chengxing Zhou +4
Large Vision-Language Models (LVLMs) typically learn visual capacity through visual instruction tuning, involving updates to both a projector and their LLM backbones. Inspired by t…
EmbSpatial-Bench: Benchmarking Spatial Understanding for Embodied Tasks with Large Vision-Language Models
Mengfei Du, Binhao Wu, Zejun Li +2
The recent rapid development of Large Vision-Language Models (LVLMs) has indicated their potential for embodied tasks.However, the critical skill of spatial understanding in embodi…
VoCoT: Unleashing Visually Grounded Multi-Step Reasoning in Large Multi-Modal Models
Zejun Li, Ruipu Luo, Jiwen Zhang +3
While large multi-modal models (LMMs) have exhibited impressive capabilities across diverse tasks, their effectiveness in handling complex tasks has been limited by the prevailing…
DELAN: Dual-Level Alignment for Vision-and-Language Navigation by Cross-Modal Contrastive Learning
Mengfei Du, Binhao Wu, Jiwen Zhang +5
Vision-and-Language navigation (VLN) requires an agent to navigate in unseen environment by following natural language instruction. For task completion, the agent needs to align an…
Android in the Zoo: Chain-of-Action-Thought for GUI Agents
Jiwen Zhang, Jihao Wu, Yihua Teng +5
Large language model (LLM) leads to a surge of autonomous GUI agents for smartphone, which completes a task triggered by natural language through predicting a sequence of actions o…