Cover Image

PepBenchmark: A Standardized Benchmark for Peptide Machine Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Jiahui, Wang, Rouyi, Zhou, Kuangqi, Xiao, Tianshu, Zhu, Lingyan, Min, Yaosen, Wang, Yang
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PepSpecBench: A Unified Evaluation Benchmark for Peptide Tandem Mass Spectrometry Prediction
by: Yang, Zhiwen, et al.
Published: (2026)

An Integrated Deep-Learning Framework for Peptide-Protein Interaction Prediction and Target-Conditioned Peptide Generation with ConGA-PepPI and TC-PepGen
by: Tang, Chupei, et al.
Published: (2026)

PepThink-R1: LLM for Interpretable Cyclic Peptide Optimization with CoT SFT and Reinforcement Learning
by: Wang, Ruheng, et al.
Published: (2025)

CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and Optimization
by: Ge, Cheng, et al.
Published: (2025)

PepHarmony: A Multi-View Contrastive Learning Framework for Integrated Sequence and Structure-Based Peptide Encoding
by: Zhang, Ruochi, et al.
Published: (2024)

Pep2Prob Benchmark: Predicting Fragment Ion Probability for MS$^2$-based Proteomics
by: Xu, Hao, et al.
Published: (2025)

Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and Directions
by: Wang, Xin, et al.
Published: (2022)

MIPS: a Multimodal Infinite Polymer Sequence Pre-training Framework for Polymer Property Prediction
by: Wang, Jiaxi, et al.
Published: (2025)

PepEVOLVE: Position-Aware Dynamic Peptide Optimization via Group-Relative Advantage
by: Nguyen, Trieu, et al.
Published: (2025)

DapPep: Domain Adaptive Peptide-agnostic Learning for Universal T-cell Receptor-antigen Binding Affinity Prediction
by: Zheng, Jiangbin, et al.
Published: (2024)

Benchmarking General-Purpose In-Context Learning
by: Wang, Fan, et al.
Published: (2024)

AMIGO: Agentic Multi-Image Grounding Oracle Benchmark
by: Wang, Min, et al.
Published: (2026)

Meta-World+: An Improved, Standardized, RL Benchmark
by: McLean, Reginald, et al.
Published: (2025)

Guidance Design for Escape Flight Vehicle Using Evolution Strategy Enhanced Deep Reinforcement Learning
by: Hu, Xiao, et al.
Published: (2024)

LoRALib: A Standardized Benchmark for Evaluating LoRA-MoE Methods
by: Wang, Shaoheng, et al.
Published: (2025)

WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking
by: Liu, Yunchao, et al.
Published: (2024)

Interactive Benchmarks
by: Yue, Baoqing, et al.
Published: (2026)

TabArena: A Living Benchmark for Machine Learning on Tabular Data
by: Erickson, Nick, et al.
Published: (2025)

Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning
by: Zhu, Jing, et al.
Published: (2024)

How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning
by: Wang, Yuanyuan, et al.
Published: (2024)

HEARTS: Benchmarking LLM Reasoning on Health Time Series
by: Li, Sirui, et al.
Published: (2026)

Safety-Gymnasium: A Unified Safe Reinforcement Learning Benchmark
by: Ji, Jiaming, et al.
Published: (2023)

CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
by: Liu, Zhining, et al.
Published: (2025)

Benchmarking Post-Training Quantization in LLMs: Comprehensive Taxonomy, Unified Evaluation, and Comparative Analysis
by: Zhao, Jiaqi, et al.
Published: (2025)

RamanBench: A Large-Scale Benchmark for Machine Learning on Raman Spectroscopy
by: Koddenbrock, Mario, et al.
Published: (2026)

A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
by: Shmuel, Assaf, et al.
Published: (2024)

DTR-Bench: An in silico Environment and Benchmark Platform for Reinforcement Learning Based Dynamic Treatment Regime
by: Luo, Zhiyao, et al.
Published: (2024)

NS-Pep: De novo Peptide Design with Non-Standard Amino Acids
by: Guo, Tao, et al.
Published: (2025)

BalanceBenchmark: A Survey for Multimodal Imbalance Learning
by: Xu, Shaoxuan, et al.
Published: (2025)

ExEBench: Benchmarking Foundation Models on Extreme Earth Events
by: Zhao, Shan, et al.
Published: (2025)

TSI-Bench: Benchmarking Time Series Imputation
by: Du, Wenjie, et al.
Published: (2024)

Benchmarking On-Device Machine Learning on Apple Silicon with MLX
by: Ajayi, Oluwaseun A., et al.
Published: (2025)

Deep Unlearn: Benchmarking Machine Unlearning for Image Classification
by: Cadet, Xavier F., et al.
Published: (2024)

CausalProfiler: Generating Synthetic Benchmarks for Rigorous and Transparent Evaluation of Causal Machine Learning
by: Panayiotou, Panayiotis, et al.
Published: (2025)

ODRL: A Benchmark for Off-Dynamics Reinforcement Learning
by: Lyu, Jiafei, et al.
Published: (2024)

A Comprehensive Graph Pooling Benchmark: Effectiveness, Robustness and Generalizability
by: Wang, Pengyun, et al.
Published: (2024)

W2SAT: Learning to generate SAT instances from Weighted Literal Incidence Graphs
by: Wen, Weihuang, et al.
Published: (2023)

Benchmarking Active Learning for NILM
by: Patel, Dhruv, et al.
Published: (2024)

CLoG: Benchmarking Continual Learning of Image Generation Models
by: Zhang, Haotian, et al.
Published: (2024)

Benchmark Success, Clinical Failure: When Reinforcement Learning Optimizes for Benchmarks, Not Patients
by: Berger, Armin, et al.
Published: (2025)