Cover Image

LLMs Outperform Experts on Challenging Biology Benchmarks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Justen, Lennart
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Quantitative Methods
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

BioMaze: Benchmarking and Enhancing Large Language Models for Biological Pathway Reasoning
by: Zhao, Haiteng, et al.
Published: (2025)

AssayBench: An Assay-Level Virtual Cell Benchmark for LLMs and Agents
by: De Brouwer, Edward, et al.
Published: (2026)

Topology-Aware Multiscale Mixture of Experts for Efficient Molecular Property Prediction
by: Nguyen, Long D., et al.
Published: (2026)

MEXA-CTP: Mode Experts Cross-Attention for Clinical Trial Outcome Prediction
by: Zhang, Yiqing, et al.
Published: (2025)

BioArc: Discovering Optimal Neural Architectures for Biological Foundation Models
by: Fang, Yi, et al.
Published: (2025)

Empowering Chemical Structures with Biological Insights for Scalable Phenotypic Virtual Screening
by: Lian, Xiaoqing, et al.
Published: (2026)

Injecting Hierarchical Biological Priors into Graph Neural Networks for Flow Cytometry Prediction
by: Mojarrad, Fatemeh Nassajian, et al.
Published: (2024)

Sparsity is All You Need: Rethinking Biological Pathway-Informed Approaches in Deep Learning
by: Caranzano, Isabella, et al.
Published: (2025)

Self-Improvement Imitation with Biologically Guided Search for Protein Design Under Oracle Budgets
by: Khanna, Ashima, et al.
Published: (2026)

Leveraging Large Language Models to Predict Antibody Biological Activity Against Influenza A Hemagglutinin
by: Barkan, Ella, et al.
Published: (2025)

Protein Structure Tokenization: Benchmarking and New Recipe
by: Yuan, Xinyu, et al.
Published: (2025)

Sample-Efficient Adaptation of Drug-Response Models to Patient Tumors under Strong Biological Domain Shift
by: Cortes, Camille Jimenez, et al.
Published: (2026)

Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks
by: Deng, Alana, et al.
Published: (2026)

Chaining thoughts and LLMs to learn DNA structural biophysics
by: Ross, Tyler D., et al.
Published: (2024)

Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating and Programming Biology at All Levels
by: Song, Le, et al.
Published: (2024)

LLMs for Drug-Drug Interaction Prediction: A Comprehensive Comparison
by: De Vito, Gabriele, et al.
Published: (2025)

Incorporating Metabolic Information into LLMs for Anomaly Detection in Clinical Time-Series
by: Rahman, Maxx Richard, et al.
Published: (2024)

DeepProtein: Deep Learning Library and Benchmark for Protein Sequence Learning
by: Xie, Jiaqing, et al.
Published: (2024)

scDrugMap: Benchmarking Large Foundation Models for Drug Response Prediction
by: Wang, Qing, et al.
Published: (2025)

Benchmark on Drug Target Interaction Modeling from a Drug Structure Perspective
by: Zhang, Xinnan, et al.
Published: (2024)

Empowering LLMs for Structure-Based Drug Design via Exploration-Augmented Latent Inference
by: Hu, Xuanning, et al.
Published: (2026)

Comparison of Optimised Geometric Deep Learning Architectures, over Varying Toxicological Assay Data Environments
by: Kalian, Alexander D., et al.
Published: (2025)

Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?
by: Zheng, Kangyu, et al.
Published: (2024)

Limitations of Sequence-Based Protein Representations for Parkinson's Disease Classification: A Leakage-Free Benchmark
by: Núñez-Prado, César Jesús, et al.
Published: (2026)

A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era
by: Li, Zongru, et al.
Published: (2026)

Prostate-VarBench: A Benchmark with Interpretable TabNet Framework for Prostate Cancer Variant Classification
by: Tavara, Abraham Francisco Arellano, et al.
Published: (2025)

EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting
by: Panja, Madhurima, et al.
Published: (2026)

General Protein Pretraining or Domain-Specific Designs? Benchmarking Protein Modeling on Realistic Applications
by: Yan, Shuo, et al.
Published: (2025)

Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions
by: Sun, Rui, et al.
Published: (2024)

FGBench: A Dataset and Benchmark for Molecular Property Reasoning at Functional Group-Level in Large Language Models
by: Liu, Xuan, et al.
Published: (2025)

CaliciBoost: Performance-Driven Evaluation of Molecular Representations for Caco-2 Permeability Prediction
by: Van Le, Huong, et al.
Published: (2025)

Uncertainty-Aware Metabolic Stability Prediction with Dual-View Contrastive Learning
by: Guo, Peijin, et al.
Published: (2025)

HyboWaveNet: Hyperbolic Graph Neural Networks with Multi-Scale Wavelet Transform for Protein-Protein Interaction Prediction
by: Yu, Qingzhi, et al.
Published: (2025)

Physics-Informed Machine Learning in Biomedical Science and Engineering
by: Ahmadi, Nazanin, et al.
Published: (2025)

LAMP-PRo: Label-aware Attention for Multi-label Prediction of DNA- and RNA-binding Proteins using Protein Language Models
by: Ghosh, Nimisha, et al.
Published: (2025)

BioCube: A Multimodal Dataset for Biodiversity Research
by: Stasinos, Stylianos, et al.
Published: (2025)

Multimodal AI predicts clinical outcomes of drug combinations from preclinical data
by: Huang, Yepeng, et al.
Published: (2025)

Surrogate modeling of Cellular-Potts Agent-Based Models as a segmentation task using the U-Net neural network architecture
by: Comlekoglu, Tien, et al.
Published: (2025)

Informing Acquisition Functions via Foundation Models for Molecular Discovery
by: Chen, Qi, et al.
Published: (2025)

Self-Supervised Learning on Molecular Graphs: A Systematic Investigation of Masking Design
by: Yang, Jiannan, et al.
Published: (2025)