6 citations · 14 across the 5 of their papers we have counts for
5 papers
HalluMat: Detecting Hallucinations in LLM-Generated Materials Science Content Through Multi-Stage Verification
Bhanu Prakash Vangala, Sajid Mahmud, Pawan Neupane +2
Artificial Intelligence (AI), particularly Large Language Models (LLMs), is transforming scientific discovery, enabling rapid knowledge generation and hypothesis formulation. Howev…
PSBench: a large-scale benchmark for estimating the accuracy of protein complex structural models
Pawan Neupane, Jian Liu, Jianlin Cheng
Predicting protein complex structures is essential for protein function analysis, protein design, and drug discovery. While AI methods like AlphaFold can predict accurate structura…
FlowDock: Geometric Flow Matching for Generative Protein-Ligand Docking and Affinity Prediction
Alex Morehead, Jianlin Cheng
Powerful generative AI models of protein-ligand structure have recently been proposed, but few of these methods support both flexible protein-ligand docking and affinity estimation…
Evaluating representation learning on the protein structure universe
Arian R. Jamasb, Alex Morehead, Chaitanya K. Joshi +8
We introduce ProteinWorkshop, a comprehensive benchmark suite for representation learning on protein structures with Geometric Graph Neural Networks. We consider large-scale pre-tr…
Adapting Segment Anything Model (SAM) through Prompt-based Learning for Enhanced Protein Identification in Cryo-EM Micrographs
Fei He, Zhiyuan Yang, Mingyue Gao +6
Cryo-electron microscopy (cryo-EM) remains pivotal in structural biology, yet the task of protein particle picking, integral for 3D protein structure construction, is laden with ma…