{"total":23,"rows":[{"id":"2503.04176","title":"TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records","created":"2025-03-06","cited_by_count":34,"area":null},{"id":"2410.22812","title":"Universality of the $\\pi^2/6$ Pathway in Avoiding Model Collapse","created":"2024-10-30","cited_by_count":26,"area":null},{"id":"2510.05197","title":"Efficient Prediction of Pass@k Scaling in Large Language Models","created":"2025-10-06","cited_by_count":16,"area":null},{"id":"2502.08924","title":"Escaping Collapse: The Strength of Weak Data for Large Language Model Training","created":"2025-02-13","cited_by_count":11,"area":null},{"id":"2506.19882","title":"Position: Machine Learning Conferences Should Establish a \"Refutations and Critiques\" Track","created":"2025-06-24","cited_by_count":7,"area":null},{"id":"2505.21677","title":"What happens when generative AI models train recursively on each others' outputs?","created":"2025-05-27","cited_by_count":6,"area":null},{"id":"2412.14872","title":"Theoretical Proof that Auto-regressive Language Models Collapse when Real-world Data is a Finite Set","created":"2024-12-19","cited_by_count":4,"area":null},{"id":"2504.03814","title":"Recursive Training Loops in LLMs: How training data properties modulate distribution shift in generated data?","created":"2025-04-04","cited_by_count":2,"area":null},{"id":"2509.23963","title":"Evaluating the Robustness of Chinchilla Compute-Optimal Scaling","created":"2025-09-28","cited_by_count":2,"area":null},{"id":"2601.05184","title":"Observations and Remedies for Large Language Model Bias in Self-Consuming Performative Loop","created":"2026-01-08","cited_by_count":2,"area":null},{"id":"2601.05280","title":"Large Language Models are Shannon Lossy Compressors Not Solomonoff Induction Estimators: Self-improvement and Singularity Are Not Near Without Symbolic Model Synthesis","created":"2026-01-05","cited_by_count":1,"area":null},{"id":"2607.08252","title":"A Multi-Timescale Recursive Self-Improvement Engine for Open-Ended Persona Growth","created":"2026-07-09","cited_by_count":1,"area":null},{"id":"2609.32987","title":"Maximum Likelihood Estimation for Entity Ranking under Iterative Synthetic Data Augmentation","created":"2026-09-26","cited_by_count":1,"area":null},{"id":"2410.18194","title":"ZIP-FIT: Embedding-Free Data Selection via Compression-Based Alignment","created":"2024-10-23","cited_by_count":0,"area":null},{"id":"2506.23979","title":"TaP: A Taxonomy-Guided Framework for Automated and Scalable Preference Data Generation","created":"2025-06-30","cited_by_count":0,"area":null},{"id":"2606.02339","title":"Entropy Minimization without Model Collapse: Mitigating Prediction Bias in Medical Imaging","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2608.19230","title":"When AI Writes, Who Gets Cited? Evidence of Citation Monoculture Across Language Models","created":"2026-08-03","cited_by_count":0,"area":null},{"id":"2608.31091","title":"Minimax bounds for watermarked and masked recursive discrete distribution estimation","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.11149","title":"Break Step: Recursive Training Resonates with Replayed Sampling Noise","created":"2026-09-10","cited_by_count":0,"area":null},{"id":"2609.18560","title":"The evolution of sex for artificial intelligence: a population-genetic framework for multigenerational model populations","created":"2026-09-16","cited_by_count":0,"area":null},{"id":"2609.34257","title":"Recursive LLM Degradation in Biomedical Question Answering: A Cross-Generation Study","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.40295","title":"How Much Is an AI Token Worth? Scaling Laws for Wild AI-Generated Web Text","created":"2026-09-30","cited_by_count":0,"area":null},{"id":"2610.15617","title":"Screening Collapse under Recursive Synthetic Data","created":"2026-10-11","cited_by_count":0,"area":null}],"next_cursor":null}