5 papers
Mitigating Overthinking in Large Reasoning Models via Difficulty-aware Reinforcement Learning
Qian Wan, Ziao Xu, Luona Wei +2
Large Reasoning Models (LRMs) achieve explicit chain-of-thought expansion by imitating deep thinking behaviors of humans, demonstrating excellent performance in complex task scenar…
Beyond Error-Based Optimization: Experience-Driven Symbolic Regression with Goal-Conditioned Reinforcement Learning
Jianwen Sun, Xinrui Li, Fuqing Li +1
Symbolic Regression aims to automatically identify compact and interpretable mathematical expressions that model the functional relationship between input and output variables. Mos…
Evolvable Psychology Informed Neural Network for Memory Behavior Modeling
Xiaoxuan Shen, Zhihai Hu, Qirong Chen +3
Memory behavior modeling is a core issue in cognitive psychology and education. Classical psychological theories typically use memory equations to describe memory behavior, which e…
COMET: "Cone of experience" enhanced large multimodal model for mathematical problem generation
Sannyuya Liu, Jintian Feng, Zongkai Yang +4
The automatic generation of high-quality mathematical problems is practically valuable in many educational scenarios. Large multimodal model provides a novel technical approach for…
Automated discovery of symbolic laws governing skill acquisition from naturally occurring data
Sannyuya Liu, Qing Li, Xiaoxuan Shen +2
Skill acquisition is a key area of research in cognitive psychology as it encompasses multiple psychological processes. The laws discovered under experimental paradigms are controv…