{"total":16,"rows":[{"id":"2509.25149","title":"Pretraining Large Language Models with NVFP4","created":"2025-09-29","cited_by_count":76,"area":null},{"id":"2510.23081","title":"A Survey on LLM Mid-Training","created":"2025-10-27","cited_by_count":21,"area":null},{"id":"2505.18091","title":"Data Mixing Can Induce Phase Transitions in Knowledge Acquisition","created":"2025-05-23","cited_by_count":16,"area":null},{"id":"2505.24844","title":"Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning","created":"2025-05-30","cited_by_count":14,"area":null},{"id":"2510.14865","title":"Midtraining Bridges Pretraining and Posttraining Distributions","created":"2025-10-16","cited_by_count":12,"area":null},{"id":"2505.12534","title":"ChemPile: A 250GB Diverse and Curated Dataset for Chemical Foundation Models","created":"2025-05-18","cited_by_count":9,"area":null},{"id":"2509.25087","title":"Scaling with Collapse: Efficient and Predictable Training of LLM Families","created":"2025-09-29","cited_by_count":9,"area":null},{"id":"2503.07879","title":"Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality","created":"2025-03-10","cited_by_count":8,"area":null},{"id":"2506.11389","title":"Curriculum-Guided Layer Scaling for Language Model Pretraining","created":"2025-06-13","cited_by_count":4,"area":null},{"id":"2605.22769","title":"Understanding Data Temporality Impact on Large Language Models Pre-training","created":"2026-05-21","cited_by_count":3,"area":null},{"id":"2509.25380","title":"Predicting Training Re-evaluation Curves Enables Effective Data Curriculums for LLMs","created":"2025-09-29","cited_by_count":2,"area":null},{"id":"2602.00747","title":"Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training","created":"2026-01-31","cited_by_count":2,"area":null},{"id":"2603.29522","title":"Baby Scale: Investigating Models Trained on Individual Children's Language Input","created":"2026-03-31","cited_by_count":2,"area":null},{"id":"2606.18663","title":"RegMix-D: Dynamic Data Mixing via Proxy Training Trajectories","created":"2026-06-17","cited_by_count":2,"area":null},{"id":"2608.13482","title":"Synthetic Persona Pretraining: Alignment from Token Zero","created":"2026-08-13","cited_by_count":1,"area":null},{"id":"2610.09611","title":"Sequential Pretraining Favors Large Models","created":"2026-10-07","cited_by_count":0,"area":null}],"next_cursor":null}