5 citations · 6 across the 3 of their papers we have counts for
4 papers
PiSA: A Self-Augmented Data Engine and Training Strategy for 3D Understanding with Large Models
Zilu Guo, Hongbin Lin, Zhihao Yuan +6
3D Multimodal Large Language Models (MLLMs) have recently made substantial advancements. However, their potential remains untapped, primarily due to the limited quantity and subopt…
MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines
Dongzhi Jiang, Renrui Zhang, Ziyu Guo +11
The advent of Large Language Models (LLMs) has paved the way for AI search engines, e.g., SearchGPT, showcasing a new paradigm in human-internet interaction. However, most current…
Scenarios and Approaches for Situated Natural Language Explanations
Pengshuo Qiu, Frank Rudzicz, Zining Zhu
Large language models (LLMs) can be used to generate natural language explanations (NLE) that are adapted to different users' situations. However, there is yet to be a quantitative…
MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
Renrui Zhang, Dongzhi Jiang, Yichi Zhang +8
The remarkable progress of Multi-modal Large Language Models (MLLMs) has garnered unparalleled attention, due to their superior performance in visual contexts. However, their capab…