activity
20232026
most citedNatural Language-Assisted Multi-modal Medication Recommendation

8 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery

Mingze Li, Yu Rong, Songyou Li +16

Artificial intelligence has accelerated materials discovery through high-throughput prediction and generation, yet the decision problem remains a formidable bottleneck. While curre…

q-bio.QM2026

Lingshu-Cell: A generative cellular world model for transcriptome modeling toward virtual cells

Han Zhang, Guo-Hua Yuan, Chaohao Yuan +6

Modeling cellular states and predicting their responses to perturbations are central challenges in computational biology and the development of virtual cells. Existing foundation m…

cs.LG2026

IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck

Tian Bian, Yifan Niu, Chaohao Yuan +7

Circuit discovery has recently attracted attention as a potential research direction to explain the non-trivial behaviors of language models. It aims to find the computational subg…

cs.AI2025★ 8 cited

Natural Language-Assisted Multi-modal Medication Recommendation

Jie Tan, Yu Rong, Kangfei Zhao +5

Combinatorial medication recommendation(CMR) is a fundamental task of healthcare, which offers opportunities for clinical physicians to provide more precise prescriptions for patie…

cs.CY2023

Language Agents for Detecting Implicit Stereotypes in Text-to-image Models at Scale

Qichao Wang, Tian Bian, Yian Yin +6

The recent surge in the research of diffusion models has accelerated the adoption of text-to-image models in various Artificial Intelligence Generated Content (AIGC) commercial pro…