6 papers
Library Reachability in LSR-Synth: How Anti-Memorization Design Changes the Measurement of Symbolic Discovery
Zhan'ao Yao, Liang Yin, Zhihao Gao +9
Existing benchmarks for scientific equation discovery are largely composed of well-known equations available in the public domain, making it difficult to determine whether a model…
MatMind: A Structure-Activity Knowledge-Driven Generative Foundation Model for Materials Science
Zhan'ao Yao, Boxuan Zhang, Jingyuan Shu +10
Progress in AI-driven crystal materials science has so far been carried by narrow architectures purpose-built for individual tasks -- graph neural networks for property prediction,…
Design Conditions for Intra-Group Learning of Sequence-Level Rewards: Token Gradient Cancellation
Fei Ding, Yongkang Zhang, youwei wang +1
Reinforcement learning for multi-step reasoning with large language models (LLMs) typically relies on sparse terminal rewards, which creates a poorly conditioned credit-assignment…
Difference Feedback: Generating Multimodal Process-Level Supervision for VLM Reinforcement Learning
Feiding, Yongkang Zhang, Yuhao Liao +10
Vision--language models (VLMs) are increasingly aligned via Group Relative Policy Optimization (GRPO)-style training. However, relying solely on terminal outcome rewards yields spa…
Multi-Layer GRPO: Enhancing Reasoning and Self-Correction in Large Language Models
Fei Ding, Baiqiao Wang, Zijian Zeng +1
The Group Relative Policy Optimization (GRPO) algorithm has demonstrated considerable success in enhancing the reasoning capabilities of large language models (LLMs), as evidenced…
Deep Sparse Latent Feature Models for Knowledge Graph Completion
Haotian Li, Rui Zhang, Lingzhi Wang +6
Recent advances in knowledge graph completion (KGC) have emphasized text-based approaches to navigate the inherent complexities of large-scale knowledge graphs (KGs). While these m…