2 citations · 6 across the 13 of their papers we have counts for
6 papers · 1 filter
SPARTUN3D: Situated Spatial Understanding of 3D World in Large Language Models
Yue Zhang, Zhiyang Xu, Ying Shen +2
Integrating the 3D world into large language models (3D-based LLMs) has been a promising research direction for 3D scene understanding. However, current 3D-based LLMs fall short in…
Modality-Specialized Synergizers for Interleaved Vision-Language Generalists
Zhiyang Xu, Minqian Liu, Ying Shen +5
Recent advancements in Vision-Language Models (VLMs) have led to the emergence of Vision-Language Generalists (VLGs) capable of understanding and generating both text and images. H…
InternalInspector : Robust Confidence Estimation in LLMs through Internal States
Mohammad Beigi, Ying Shen, Runing Yang +7
Despite their vast capabilities, Large Language Models (LLMs) often struggle with generating reliable outputs, frequently producing high-confidence inaccuracies known as hallucinat…
Many-to-many Image Generation with Auto-regressive Diffusion Models
Ying Shen, Yizhe Zhang, Shuangfei Zhai +3
Recent advancements in image generation have made significant progress, yet existing models present limitations in perceiving and generating an arbitrary number of interrelated ima…
Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning
Zhiyang Xu, Chao Feng, Rulin Shao +6
Despite vision-language models' (VLMs) remarkable capabilities as versatile visual assistants, two substantial challenges persist within the existing VLM frameworks: (1) lacking ta…
Multimodal Instruction Tuning with Conditional Mixture of LoRA
Ying Shen, Zhiyang Xu, Qifan Wang +3
Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in diverse tasks across different domains, with an increasing focus on improving their zero-shot g…