6 papers
MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback
Zehong Wang, Yijun Ma, Connor R. Schmidt +7
Molecular dynamics (MD) is the canonical in-silico method for atomistic molecular science, simulating molecular behavior from first-principle physics. Designing an MD pipeline for…
ProPlay: Procedural World Models for Self-Evolving LLM Agents
Yijun Ma, Zehong Wang, Yiyang Li +5
Self-evolving agents are expected to improve through interaction without external supervision, but this remains difficult in partially observable environments where agents must exp…
Same Signal, Opposite Meaning: Direction-Informed Adaptive Learning for LLM Agents
Ziming Li, Jiatan Huang, Xiaoguang Guo +2
Adaptive test-time compute for LLM agents aims to invoke extra computation only when it improves performance. Existing methods typically use confidence-, uncertainty-, or difficult…
On the Safety of Graph Representation Learning
Xiaoguang Guo, Zehong Wang, Ziming Li +5
Graph representation learning (GRL) has evolved from topology-only graph embeddings to task-specific supervised GNNs, and more recently to reusable representations and graph founda…
Generalizing GNNs with Tokenized Mixture of Experts
Xiaoguang Guo, Zehong Wang, Jiazheng Li +5
Deployed graph neural networks (GNNs) are frozen at deployment yet must fit clean data, generalize under distribution shifts, and remain stable to perturbations. We show that stati…
Molecular Representations in Implicit Functional Space via Hyper-Networks
Zehong Wang, Xiaolong Han, Qi Yang +10
Molecular representations fundamentally shape how machine learning systems reason about molecular structure and physical properties. Most existing approaches adopt a discrete pipel…