{"total":33,"rows":[{"id":"2306.15794","title":"HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution","created":"2023-06-27","cited_by_count":194,"area":null},{"id":"2304.03208","title":"Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster","created":"2023-04-06","cited_by_count":109,"area":null},{"id":"2312.16903","title":"Spike No More: Stabilizing the Pre-training of Large Language Models","created":"2023-12-28","cited_by_count":52,"area":null},{"id":"2303.10464","title":"SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models","created":"2023-03-18","cited_by_count":28,"area":null},{"id":"2304.03589","title":"On Efficient Training of Large-Scale Deep Learning Models: A Literature Review","created":"2023-04-07","cited_by_count":26,"area":null},{"id":"2312.00678","title":"The Efficiency Spectrum of Large Language Models: An Algorithmic Survey","created":"2023-12-01","cited_by_count":26,"area":null},{"id":"2405.13226","title":"Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum","created":"2024-05-21","cited_by_count":26,"area":null},{"id":"2306.09539","title":"Block-State Transformers","created":"2023-06-15","cited_by_count":24,"area":null},{"id":"2407.10194","title":"Curriculum Learning for Small Code Language Models","created":"2024-07-14","cited_by_count":22,"area":null},{"id":"2310.15389","title":"Irreducible Curriculum for Language Model Pretraining","created":"2023-10-23","cited_by_count":16,"area":null},{"id":"2212.03597","title":"DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing","created":"2022-12-07","cited_by_count":13,"area":null},{"id":"2402.04286","title":"Progress and Opportunities of Foundation Models in Bioinformatics","created":"2024-02-06","cited_by_count":13,"area":null},{"id":"2305.15096","title":"Dynamic Masking Rate Schedules for MLM Pretraining","created":"2023-05-24","cited_by_count":12,"area":null},{"id":"2410.00131","title":"Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models","created":"2024-09-30","cited_by_count":6,"area":null},{"id":"2503.15450","title":"SkyLadder: Better and Faster Pretraining via Context Window Scheduling","created":"2025-03-19","cited_by_count":6,"area":null},{"id":"2601.21698","title":"Curriculum Learning for LLM Pretraining: An Analysis of Learning Dynamics","created":"2026-01-29","cited_by_count":6,"area":null},{"id":"2406.05418","title":"Multi-attribute Auction-based Resource Allocation for Twins Migration in Vehicular Metaverses: A GPT-based DRL Approach","created":"2024-06-08","cited_by_count":5,"area":null},{"id":"2410.05052","title":"Initialization of Large Language Models via Reparameterization to Mitigate Loss Spikes","created":"2024-10-07","cited_by_count":4,"area":null},{"id":"2412.21124","title":"Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism","created":"2024-12-30","cited_by_count":4,"area":null},{"id":"2504.09844","title":"MegaScale-Data: Scaling Dataloader for Multisource Large Foundation Model Training","created":"2025-04-14","cited_by_count":4,"area":null},{"id":"2310.15672","title":"How Much Context Does My Attention-Based ASR System Need?","created":"2023-10-24","cited_by_count":3,"area":null},{"id":"2508.15475","title":"Influence-driven Curriculum Learning for Pre-training on Limited Data","created":"2025-08-21","cited_by_count":2,"area":null},{"id":"2212.11511","title":"Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene Understanding","created":"2022-12-22","cited_by_count":1,"area":null},{"id":"2409.15697","title":"dnaGrinder: a lightweight and high-capacity genomic foundation model","created":"2024-09-24","cited_by_count":1,"area":null},{"id":"2410.07563","title":"PLaMo-100B: A Ground-Up Language Model Designed for Japanese Proficiency","created":"2024-10-10","cited_by_count":1,"area":null},{"id":"2510.23241","title":"Progressive Growing of Patch Size: Curriculum Learning for Accelerated and Improved Medical Image Segmentation","created":"2025-10-27","cited_by_count":1,"area":null},{"id":"2604.00199","title":"QUEST: A robust attention formulation using query-modulated spherical attention","created":"2026-03-31","cited_by_count":1,"area":null},{"id":"2403.00952","title":"MediSwift: Efficient Sparse Pre-trained Biomedical Language Models","created":"2024-03-01","cited_by_count":0,"area":null},{"id":"2503.01564","title":"Attention Condensation via Sparsity Induced Regularized Training","created":"2025-03-03","cited_by_count":0,"area":null},{"id":"2511.09571","title":"General Intelligence-based Fragmentation (GIF): A framework for peak-labeled spectra simulation","created":"2025-11-11","cited_by_count":0,"area":null},{"id":"2511.12103","title":"BdSL-SPOTER: A Transformer-Based Framework for Bengali Sign Language Recognition with Cultural Adaptation","created":"2025-11-15","cited_by_count":0,"area":null},{"id":"2604.27124","title":"Better Models, Faster Training: Sigmoid Attention for single-cell Foundation Models","created":"2026-04-29","cited_by_count":0,"area":null},{"id":"2609.06218","title":"Branch-Centric Tokenization and Test-Time Augmentation for Skeleton Generation","created":"2026-09-05","cited_by_count":0,"area":null}],"next_cursor":null}