8 papers
LiveK12Bench: Have Large Multimodal Models Truly Conquered High School-level Examinations?
Xiaohan Wang, Mingze Yin, Yilin Zhao +2
Advanced Large Multimodal Models (LMMs) have demonstrated impressive performance in K-12 reasoning tasks, exhibiting great promise as intelligent tutors. Realizing this potential r…
Concise Geometric Description as a Bridge: Unleashing the Potential of LLM for Plane Geometry Problem Solving
Jingyun Wang, Dian Li, Xiaohan Wang +3
Plane Geometry Problem Solving (PGPS) is a multimodal reasoning task that aims to solve a plane geometric problem based on a geometric diagram and problem textual descriptions. Alt…
Learning to Pose Problems: Reasoning-Driven and Solver-Adaptive Data Synthesis
Yongxian Wei, Yilin Zhao, Zixuan Hu +7
Data synthesis for training large reasoning models offers a scalable alternative to limited, human-curated datasets, enabling the creation of high-quality data. However, existing a…
Enhancing Multimodal In-Context Learning via Inductive-Deductive Reasoning
Haoyu Wang, Haonan Wang, Yuyan Chen +5
In-context learning (ICL) allows large models to adapt to tasks using a few examples, yet its extension to vision-language models (VLMs) remains fragile. Our analysis reveals that…
Adaptive Global and Fine-Grained Perceptual Fusion for MLLM Embeddings Compatible with Hard Negative Amplification
Lexiang Hu, Youze Xue, Dian Li +2
Multimodal embeddings serve as a bridge for aligning vision and language, with the two primary implementations -- CLIP-based and MLLM-based embedding models -- both limited to capt…
Fact-R1: Towards Explainable Video Misinformation Detection with Deep Reasoning
Fanrui Zhang, Dian Li, Qiang Zhang +6
The rapid spread of multimodal misinformation on social media has raised growing concerns, while research on video misinformation detection remains limited due to the lack of large…