{"total":45,"rows":[{"id":"2103.05247","title":"Pretrained Transformers as Universal Computation Engines","created":"2021-03-09","cited_by_count":162,"area":null},{"id":"2203.06125","title":"Protein Representation Learning by Geometric Structure Pretraining","created":"2022-03-11","cited_by_count":162,"area":null},{"id":"2206.02096","title":"PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding","created":"2022-06-05","cited_by_count":77,"area":null},{"id":"2302.04611","title":"A Text-guided Protein Design Framework","created":"2023-02-09","cited_by_count":64,"area":null},{"id":"2207.12600","title":"Learning Hierarchical Protein Representations via Complete 3D Graph Networks","created":"2022-07-26","cited_by_count":55,"area":null},{"id":"2204.02337","title":"Multi-Scale Representation Learning on Proteins","created":"2022-04-04","cited_by_count":52,"area":null},{"id":"2401.06199","title":"xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein","created":"2024-01-11","cited_by_count":50,"area":null},{"id":"2301.06568","title":"Ankh: Optimized Protein Language Model Unlocks General-Purpose Modelling","created":"2023-01-16","cited_by_count":45,"area":null},{"id":"2204.04213","title":"Structure-aware Protein Self-supervised Learning","created":"2022-04-06","cited_by_count":33,"area":null},{"id":"2205.15675","title":"Contrastive Representation Learning for 3D Protein Structures","created":"2022-05-31","cited_by_count":30,"area":null},{"id":"2402.08703","title":"A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation","created":"2024-02-13","cited_by_count":29,"area":null},{"id":"2310.03269","title":"InstructProtein: Aligning Human and Protein Language via Knowledge Instruction","created":"2023-10-05","cited_by_count":28,"area":null},{"id":"2306.09375","title":"Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials","created":"2023-06-15","cited_by_count":22,"area":null},{"id":"2203.16939","title":"Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs","created":"2022-03-31","cited_by_count":16,"area":null},{"id":"2406.13864","title":"Evaluating representation learning on the protein structure universe","created":"2024-06-19","cited_by_count":16,"area":null},{"id":"2503.00089","title":"Protein Structure Tokenization: Benchmarking and New Recipe","created":"2025-02-28","cited_by_count":15,"area":null},{"id":"2310.11802","title":"De novo protein design using geometric vector field networks","created":"2023-10-18","cited_by_count":14,"area":null},{"id":"2301.02120","title":"Reprogramming Pretrained Language Models for Protein Sequence Representation Learning","created":"2023-01-05","cited_by_count":12,"area":null},{"id":"2401.14819","title":"Endowing Protein Language Models with Structural Knowledge","created":"2024-01-26","cited_by_count":11,"area":null},{"id":"2103.10334","title":"Structure Inducing Pre-Training","created":"2021-03-18","cited_by_count":10,"area":null},{"id":"2202.06208","title":"Improving Molecular Representation Learning with Metric Learning-enhanced Optimal Transport","created":"2022-02-13","cited_by_count":9,"area":null},{"id":"2302.12563","title":"Retrieved Sequence Augmentation for Protein Representation Learning","created":"2023-02-24","cited_by_count":7,"area":null},{"id":"2107.12460","title":"Don't Sweep your Learning Rate under the Rug: A Closer Look at Cross-modal Transfer of Pretrained Transformers","created":"2021-07-26","cited_by_count":6,"area":null},{"id":"2402.05856","title":"Structure-Informed Protein Language Model","created":"2024-02-07","cited_by_count":6,"area":null},{"id":"2404.00254","title":"Clustering for Protein Representation Learning","created":"2024-03-30","cited_by_count":6,"area":null},{"id":"2501.10282","title":"Computational Protein Science in the Era of Large Language Models (LLMs)","created":"2025-01-17","cited_by_count":6,"area":null},{"id":"2506.06294","title":"GLProtein: Global-and-Local Structure Aware Protein Representation Learning","created":"2025-05-17","cited_by_count":5,"area":null},{"id":"2301.13154","title":"Protein Representation Learning via Knowledge Enhanced Primary Structure Modeling","created":"2023-01-30","cited_by_count":3,"area":null},{"id":"2305.18558","title":"DelBugV: Delta-Debugging Neural Network Verifiers","created":"2023-05-29","cited_by_count":3,"area":null},{"id":"2410.21683","title":"Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer","created":"2024-10-29","cited_by_count":3,"area":null},{"id":"2408.00057","title":"GOProteinGNN: Leveraging Protein Knowledge Graphs for Protein Representation Learning","created":"2024-07-31","cited_by_count":2,"area":null},{"id":"2411.11530","title":"SeqProFT: Sequence-only Protein Property Prediction with LoRA Finetuning","created":"2024-11-18","cited_by_count":2,"area":null},{"id":"2505.20589","title":"Prot2Token: A Unified Framework for Protein Modeling via Next-Token Prediction","created":"2025-05-26","cited_by_count":2,"area":null},{"id":"2605.18552","title":"Protein Fold Classification at Scale: Benchmarking and Pretraining","created":"2026-05-18","cited_by_count":2,"area":null},{"id":"2410.02023","title":"DeepProtein: Deep Learning Library and Benchmark for Protein Sequence Learning","created":"2024-10-02","cited_by_count":1,"area":null},{"id":"2503.21681","title":"A Comprehensive Benchmark for RNA 3D Structure-Function Modeling","created":"2025-03-27","cited_by_count":1,"area":null},{"id":"2505.16896","title":"Structure-Aligned Protein Language Model","created":"2025-05-22","cited_by_count":1,"area":null},{"id":"2310.17415","title":"PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications","created":"2023-10-26","cited_by_count":0,"area":null},{"id":"2402.07955","title":"ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation","created":"2024-02-10","cited_by_count":0,"area":null},{"id":"2511.05020","title":"DAFM: Dynamic Adaptive Fusion for Multi-Model Collaboration in Composed Image Retrieval","created":"2025-11-07","cited_by_count":0,"area":null},{"id":"2512.06752","title":"Multi-Scale Protein Structure Modelling with Geometric Graph U-Nets","created":"2025-12-07","cited_by_count":0,"area":null},{"id":"2602.00862","title":"Towards Multiscale Graph-based Protein Learning with Geometric Secondary Structural Motifs","created":"2026-01-31","cited_by_count":0,"area":null},{"id":"2605.01625","title":"PRIME: Protein Representation via Physics-Informed Multiscale Equivariant Hierarchies","created":"2026-05-02","cited_by_count":0,"area":null},{"id":"2606.19374","title":"Protein Representation Learning with Secondary-Structure and Energy-Filtered Hydrogen-Bond Graphs","created":"2026-06-12","cited_by_count":0,"area":null},{"id":"2606.22307","title":"Enhancing Protein Representation Learning via Manifold Restore Mixing","created":"2026-06-21","cited_by_count":0,"area":null}],"next_cursor":null}