3 papers
cs.CL2025
Unlocking Multimodal Mathematical Reasoning via Process Reward Model
Ruilin Luo, Zhuofan Zheng, Yifan Wang +9
Process Reward Models (PRMs) have shown promise in enhancing the mathematical reasoning capabilities of Large Language Models (LLMs) through Test-Time Scaling (TTS). However, their…
cs.CL2024
Exploring the Mystery of Influential Data for Mathematical Reasoning
Xinzhe Ni, Yeyun Gong, Zhibin Gou +4
Selecting influential data for fine-tuning on downstream tasks is a key factor for both performance and computation efficiency. Recent works have shown that training with only limi…
cs.LG2024
Incremental Residual Concept Bottleneck Models
Chenming Shang, Shiji Zhou, Hengyuan Zhang +3
Concept Bottleneck Models (CBMs) map the black-box visual representations extracted by deep neural networks onto a set of interpretable concepts and use the concepts to make predic…