most citedLang2Str: Two-Stage Crystal Structure Generation with LLMs and Continuous Flow Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

q-bio.QM2026

ProtDBench: A Unified Benchmark of Protein Binder Design and Evaluation

Cong Liu, Milong Ren, Jiaqi Guan +4

Recent advances in de novo protein binder design have enabled increasing experimental validation, yet reported in silico metrics remain difficult to interpret or compare across stu…

q-bio.QM2026

A-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion

Chaoran Cheng, Jiaqi Guan, Milong Ren +5

We present A-CODE, a fully atomic unified one-stage protein co-design model that simultaneously refines discrete atom types and continuous atom coordinates. Unlike predominant two-…

cs.LG2026

Lang2Str: Two-Stage Crystal Structure Generation with LLMs and Continuous Flow Models

Cong Liu, Chengyue Gong, Zhenyu Liu +2

Generative models hold great promise for accelerating material discovery but are often limited by their inflexible single-stage generative process in designing valid and diverse ma…

cond-mat.mtrl-sci2025

XDXD: End-to-end crystal structure determination with low resolution X-ray diffraction

Jiale Zhao, Cong Liu, Yuxuan Zhang +4

Determining crystal structures from X-ray diffraction data is fundamental across diverse scientific fields, yet remains a significant challenge when data is limited to low resoluti…

q-bio.QM2025

Protenix-Mini+: efficient structure prediction model with scalable pairformer

Bo Qiang, Chengyue Gong, Xinshi Chen +2

Lightweight inference is critical for biomolecular structure prediction and downstream tasks, enabling efficient real-world deployment and inference-time scaling for large-scale ap…

cs.LG2025

Protenix-Mini: Efficient Structure Predictor via Compact Architecture, Few-Step Diffusion and Switchable pLM

Chengyue Gong, Xinshi Chen, Yuxuan Zhang +3

Lightweight inference is critical for biomolecular structure prediction and other downstream tasks, enabling efficient real-world deployment and inference-time scaling for large-sc…