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cs.LG2026
PLDiv: Measuring Dataset Diversity and Semantic Collapse via Persistence Landscapes
Yang Ba, Michelle V. Mancenido, Rong Pan
Modern data pipelines increasingly combine human-created and human-curated data with AI-generated data for model training and evaluation. As datasets grow, they often add semantica…
cs.LG2026
Can We Trust This Evaluation? Instance-Level Reliability of LLM-as-a-Judge
Yang Ba, Michelle V. Mancenido, Rong Pan
LLM-as-a-judge evaluation commonly aggregates multiple judges' decisions into a majority vote, yet this panel decision process does not guarantee that the evaluation of an individu…
cs.LG2026
Training-Aware Target Coverage for Synthetic Data Selection
Yang Ba, Michelle V. Mancenido, Rong Pan
Synthetic data are increasingly used to scale LLM training, yet more synthetic data do not necessarily produce better models. Useful synthetic data must add information relevant to…