activity
20202026
most citedDPA-2: a large atomic model as a multi-task learner

132 citations · 270 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Euclid-Omni : A Unified Neuro-Symbolic Framework for Plane Geometry

Zhaoyu Li, Hangrui Bi, Youyuan Zhang +5

Euclidean geometry is a compelling testbed for AI reasoning, as it demands the combination of intuitive diagram understanding, axiomatic deduction, and algebraic computation. Yet,…

cs.AI2026

DreamProver: Evolving Transferable Lemma Libraries via a Wake-Sleep Theorem-Proving Agent

Youyuan Zhang, Jialiang Sun, Hangrui Bi +4

We introduce DreamProver, an agentic framework that leverages a "wake-sleep" program induction paradigm to discover reusable lemmas for formal theorem proving. Existing approaches…

physics.chem-ph2025★ 100 cited

DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials

Jinzhe Zeng, Duo Zhang, Anyang Peng +44

In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for m…

physics.chem-ph2023★ 132 cited

DPA-2: a large atomic model as a multi-task learner

Duo Zhang, Xinzijian Liu, Xiangyu Zhang +40

The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demo…

physics.chem-ph2022★ 27 cited

DPA-1: Pretraining of Attention-based Deep Potential Model for Molecular Simulation

Duo Zhang, Hangrui Bi, Fu-Zhi Dai +3

Machine learning assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation. With the accumulation of high-quality el…

physics.chem-ph2021★ 11 cited

Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction

Hangrui Bi, Hengyi Wang, Chence Shi +3

Reliably predicting the products of chemical reactions presents a fundamental challenge in synthetic chemistry. Existing machine learning approaches typically produce a reaction pr…

physics.chem-ph2020

Non-autoregressive electron flow generation for reaction prediction

Hangrui Bi, Hengyi Wang, Chence Shi +1

Reaction prediction is a fundamental problem in computational chemistry. Existing approaches typically generate a chemical reaction by sampling tokens or graph edits sequentially,…