5 papers
ChartMaster: Advancing Chart-to-Code Generation with Real-World Charts and Chart Similarity Reinforcement Learning
Wentao Tan, Qiong Cao, Chao Xue +3
The chart-to-code generation task requires MLLMs to convert chart images into executable code. This task faces two main challenges: limited data diversity and the difficulty of mai…
From Answers to Rationales: Self-Aligning Multimodal Reasoning with Answer-Oriented Chain-of-Thought
Wentao Tan, Qiong Cao, Yibing Zhan +2
Achieving human-like reasoning capabilities in Multimodal Large Language Models (MLLMs) has long been a goal. Current methods primarily focus on synthesizing positive rationales, t…
End-to-End HOI Reconstruction Transformer with Graph-based Encoding
Zhenrong Wang, Qi Zheng, Sihan Ma +3
With the diversification of human-object interaction (HOI) applications and the success of capturing human meshes, HOI reconstruction has gained widespread attention. Existing main…
An Atomic Skill Library Construction Method for Data-Efficient Embodied Manipulation
Dongjiang Li, Bo Peng, Chang Li +13
Embodied manipulation is a fundamental ability in the realm of embodied artificial intelligence. Although current embodied manipulation models show certain generalizations in speci…
Beyond Human Data: Aligning Multimodal Large Language Models by Iterative Self-Evolution
Wentao Tan, Qiong Cao, Yibing Zhan +2
Human preference alignment can greatly enhance Multimodal Large Language Models (MLLMs), but collecting high-quality preference data is costly. A promising solution is the self-evo…